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Of equal significance,\r\nthough perhaps less known, are its ramifications for learning theory: deep networks have\r\nbeen observed to perform surprisingly well in the high-capacity regime, aka the overfitting\r\nor underspecified regime. Classically, this regime on the far right of the bias-variance curve\r\nis associated with poor generalisation; however, recent experiments with deep networks\r\nchallenge this view.\r\n\r\nThis thesis is devoted to investigating various aspects of underspecification in deep learning.\r\nFirst, we argue that deep learning models are underspecified on two levels: a) any given\r\ntraining dataset can be fit by many different functions, and b) any given function can be\r\nexpressed by many different parameter configurations. We refer to the second kind of\r\nunderspecification as parameterisation redundancy and we precisely characterise its extent.\r\nSecond, we characterise the implicit criteria (the inductive bias) that guide learning in the\r\nunderspecified regime. Specifically, we consider a nonlinear but tractable classification\r\nsetting, and show that given the choice, neural networks learn classifiers with a large margin.\r\nThird, we consider learning scenarios where the inductive bias is not by itself sufficient to\r\ndeal with underspecification. We then study different ways of ‘tightening the specification’: i)\r\nIn the setting of representation learning with variational autoencoders, we propose a hand-\r\ncrafted regulariser based on mutual information. ii) In the setting of binary classification, we\r\nconsider soft-label (real-valued) supervision. We derive a generalisation bound for linear\r\nnetworks supervised in this way and verify that soft labels facilitate fast learning. Finally, we\r\nexplore an application of soft-label supervision to the training of multi-exit models."}],"acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"CampIT"},{"_id":"E-Lib"}],"oa_version":"Published Version","file_date_updated":"2021-05-24T11:56:02Z","department":[{"_id":"GradSch"},{"_id":"ChLa"}],"supervisor":[{"orcid":"0000-0001-8622-7887","full_name":"Lampert, Christoph","last_name":"Lampert","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph"}],"date_updated":"2023-09-08T11:11:12Z","ddc":["000"],"type":"dissertation","status":"public","_id":"9418","page":"125","date_published":"2021-05-30T00:00:00Z","doi":"10.15479/AT:ISTA:9418","date_created":"2021-05-24T13:06:23Z","has_accepted_license":"1","year":"2021","day":"30","publisher":"Institute of Science and Technology Austria","oa":1,"author":[{"last_name":"Bui Thi Mai","full_name":"Bui Thi Mai, Phuong","first_name":"Phuong","id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","title":"Underspecification in deep learning","citation":{"ista":"Phuong M. 2021. Underspecification in deep learning. Institute of Science and Technology Austria.","chicago":"Phuong, Mary. “Underspecification in Deep Learning.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/AT:ISTA:9418.","apa":"Phuong, M. (2021). Underspecification in deep learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9418","ama":"Phuong M. Underspecification in deep learning. 2021. doi:10.15479/AT:ISTA:9418","short":"M. Phuong, Underspecification in Deep Learning, Institute of Science and Technology Austria, 2021.","ieee":"M. Phuong, “Underspecification in deep learning,” Institute of Science and Technology Austria, 2021.","mla":"Phuong, Mary. Underspecification in Deep Learning. Institute of Science and Technology Austria, 2021, doi:10.15479/AT:ISTA:9418."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"department":[{"_id":"GradSch"}],"title":"Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse","external_id":{"arxiv":["2111.12171"]},"article_processing_charge":"No","author":[{"id":"2eed1f3b-896a-11ed-bdf8-93c7c4bf159e","first_name":"Illya","full_name":"Koval, Illya","last_name":"Koval"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-09-15T06:44:00Z","citation":{"short":"I. Koval, ArXiv (n.d.).","ieee":"I. Koval, “Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse,” arXiv. .","ama":"Koval I. Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. arXiv. doi:10.48550/ARXIV.2111.12171","apa":"Koval, I. (n.d.). Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. arXiv. https://doi.org/10.48550/ARXIV.2111.12171","mla":"Koval, Illya. “Local Strong Birkhoff Conjecture and Local Spectral Rigidity of Almost Every Ellipse.” ArXiv, 2111.12171, doi:10.48550/ARXIV.2111.12171.","ista":"Koval I. Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. arXiv, 2111.12171.","chicago":"Koval, Illya. “Local Strong Birkhoff Conjecture and Local Spectral Rigidity of Almost Every Ellipse.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2111.12171."},"status":"public","type":"preprint","article_number":"2111.12171","_id":"14278","date_created":"2023-09-06T08:35:43Z","date_published":"2021-11-23T00:00:00Z","doi":"10.48550/ARXIV.2111.12171","publication":"arXiv","language":[{"iso":"eng"}],"day":"23","year":"2021","publication_status":"submitted","month":"11","oa":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2111.12171"}],"oa_version":"Preprint","abstract":[{"lang":"eng","text":"The Birkhoff conjecture says that the boundary of a strictly convex integrable billiard table is necessarily an ellipse. In this article, we consider a stronger notion of integrability, namely, integrability close to the boundary, and prove a local version of this conjecture: a small perturbation of almost every ellipse that preserves integrability near the boundary, is itself an ellipse. We apply this result to study local spectral rigidity of ellipses using the connection between the wave trace of the Laplacian and the dynamics near the boundary and establish rigidity for almost all of them."}]},{"alternative_title":["ISTA Thesis"],"month":"10","abstract":[{"lang":"eng","text":"The design and verification of concurrent systems remains an open challenge due to the non-determinism that arises from the inter-process communication. In particular, concurrent programs are notoriously difficult both to be written correctly and to be analyzed formally, as complex thread interaction has to be accounted for. The difficulties are further exacerbated when concurrent programs get executed on modern-day hardware, which contains various buffering and caching mechanisms for efficiency reasons. This causes further subtle non-determinism, which can often produce very unintuitive behavior of the concurrent programs. Model checking is at the forefront of tackling the verification problem, where the task is to decide, given as input a concurrent system and a desired property, whether the system satisfies the property. The inherent state-space explosion problem in model checking of concurrent systems causes naïve explicit methods not to scale, thus more inventive methods are required. One such method is stateless model checking (SMC), which explores in memory-efficient manner the program executions rather than the states of the program. State-of-the-art SMC is typically coupled with partial order reduction (POR) techniques, which argue that certain executions provably produce identical system behavior, thus limiting the amount of executions one needs to explore in order to cover all possible behaviors. Another method to tackle the state-space explosion is symbolic model checking, where the considered techniques operate on a succinct implicit representation of the input system rather than explicitly accessing the system. In this thesis we present new techniques for verification of concurrent systems. We present several novel POR methods for SMC of concurrent programs under various models of semantics, some of which account for write-buffering mechanisms. Additionally, we present novel algorithms for symbolic model checking of finite-state concurrent systems, where the desired property of the systems is to ensure a formally defined notion of fairness."}],"acknowledged_ssus":[{"_id":"SSU"}],"oa_version":"Published Version","related_material":{"record":[{"relation":"part_of_dissertation","id":"10190","status":"public"},{"id":"10191","status":"public","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","status":"public","id":"9987"},{"id":"141","status":"public","relation":"part_of_dissertation"}]},"ec_funded":1,"publication_identifier":{"issn":["2663-337X"]},"degree_awarded":"PhD","publication_status":"published","file":[{"access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"4f412a1ee60952221b499a4b1268df35","file_id":"10225","creator":"vtoman","date_updated":"2021-11-08T14:12:22Z","file_size":2915234,"date_created":"2021-11-08T14:12:22Z","file_name":"toman_th_final.pdf"},{"file_name":"toman_thesis.zip","date_created":"2021-11-08T14:12:46Z","creator":"vtoman","file_size":8616056,"date_updated":"2021-11-09T09:00:50Z","checksum":"9584943f99127be2dd2963f6784c37d4","file_id":"10226","relation":"source_file","access_level":"closed","content_type":"application/zip"}],"language":[{"iso":"eng"}],"type":"dissertation","status":"public","keyword":["concurrency","verification","model checking"],"_id":"10199","file_date_updated":"2021-11-09T09:00:50Z","department":[{"_id":"GradSch"},{"_id":"KrCh"}],"supervisor":[{"orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"}],"date_updated":"2023-09-19T09:59:54Z","ddc":["000"],"publisher":"Institute of Science and Technology Austria","oa":1,"page":"166","doi":"10.15479/at:ista:10199","date_published":"2021-10-31T00:00:00Z","date_created":"2021-10-29T20:09:01Z","has_accepted_license":"1","year":"2021","day":"31","project":[{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","grant_number":"665385"},{"call_identifier":"FWF","_id":"25F2ACDE-B435-11E9-9278-68D0E5697425","grant_number":"S11402-N23","name":"Rigorous Systems Engineering"},{"name":"Efficient Algorithms for Computer Aided Verification","grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425"},{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","call_identifier":"H2020","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications"}],"author":[{"last_name":"Toman","orcid":"0000-0001-9036-063X","full_name":"Toman, Viktor","first_name":"Viktor","id":"3AF3DA7C-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","title":"Improved verification techniques for concurrent systems","citation":{"chicago":"Toman, Viktor. “Improved Verification Techniques for Concurrent Systems.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10199.","ista":"Toman V. 2021. Improved verification techniques for concurrent systems. Institute of Science and Technology Austria.","mla":"Toman, Viktor. Improved Verification Techniques for Concurrent Systems. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10199.","apa":"Toman, V. (2021). Improved verification techniques for concurrent systems. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10199","ama":"Toman V. Improved verification techniques for concurrent systems. 2021. doi:10.15479/at:ista:10199","ieee":"V. Toman, “Improved verification techniques for concurrent systems,” Institute of Science and Technology Austria, 2021.","short":"V. Toman, Improved Verification Techniques for Concurrent Systems, Institute of Science and Technology Austria, 2021."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"_id":"8429","type":"journal_article","article_type":"original","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","date_updated":"2023-09-26T10:36:14Z","ddc":["610"],"file_date_updated":"2021-12-06T07:47:11Z","department":[{"_id":"MaRo"}],"abstract":[{"text":"We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.","lang":"eng"}],"oa_version":"Published Version","scopus_import":"1","month":"11","intvolume":" 12","publication_identifier":{"eissn":["2041-1723"]},"publication_status":"published","file":[{"file_name":"2021_NatComm_Paxtot.pdf","date_created":"2021-12-06T07:47:11Z","creator":"cchlebak","file_size":6519771,"date_updated":"2021-12-06T07:47:11Z","success":1,"file_id":"10419","checksum":"384681be17aff902c149a48f52d13d4f","relation":"main_file","access_level":"open_access","content_type":"application/pdf"}],"language":[{"iso":"eng"}],"volume":12,"issue":"1","related_material":{"record":[{"status":"public","id":"13063","relation":"research_data"}]},"license":"https://creativecommons.org/licenses/by/4.0/","article_number":"6972","citation":{"ista":"Patxot M, Trejo Banos D, Kousathanas A, Orliac EJ, Ojavee SE, Moser G, Sidorenko J, Kutalik Z, Magi R, Visscher PM, Ronnegard L, Robinson MR. 2021. Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits. Nature Communications. 12(1), 6972.","chicago":"Patxot, Marion, Daniel Trejo Banos, Athanasios Kousathanas, Etienne J Orliac, Sven E Ojavee, Gerhard Moser, Julia Sidorenko, et al. “Probabilistic Inference of the Genetic Architecture Underlying Functional Enrichment of Complex Traits.” Nature Communications. Springer Nature, 2021. https://doi.org/10.1038/s41467-021-27258-9.","short":"M. Patxot, D. Trejo Banos, A. Kousathanas, E.J. Orliac, S.E. Ojavee, G. Moser, J. Sidorenko, Z. Kutalik, R. Magi, P.M. Visscher, L. Ronnegard, M.R. Robinson, Nature Communications 12 (2021).","ieee":"M. Patxot et al., “Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits,” Nature Communications, vol. 12, no. 1. Springer Nature, 2021.","apa":"Patxot, M., Trejo Banos, D., Kousathanas, A., Orliac, E. J., Ojavee, S. E., Moser, G., … Robinson, M. R. (2021). Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-021-27258-9","ama":"Patxot M, Trejo Banos D, Kousathanas A, et al. Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits. Nature Communications. 2021;12(1). doi:10.1038/s41467-021-27258-9","mla":"Patxot, Marion, et al. “Probabilistic Inference of the Genetic Architecture Underlying Functional Enrichment of Complex Traits.” Nature Communications, vol. 12, no. 1, 6972, Springer Nature, 2021, doi:10.1038/s41467-021-27258-9."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"full_name":"Patxot, Marion","last_name":"Patxot","first_name":"Marion"},{"last_name":"Trejo Banos","full_name":"Trejo Banos, Daniel","first_name":"Daniel"},{"first_name":"Athanasios","full_name":"Kousathanas, Athanasios","last_name":"Kousathanas"},{"first_name":"Etienne J","last_name":"Orliac","full_name":"Orliac, Etienne J"},{"last_name":"Ojavee","full_name":"Ojavee, Sven E","first_name":"Sven E"},{"first_name":"Gerhard","last_name":"Moser","full_name":"Moser, Gerhard"},{"full_name":"Sidorenko, Julia","last_name":"Sidorenko","first_name":"Julia"},{"first_name":"Zoltan","full_name":"Kutalik, Zoltan","last_name":"Kutalik"},{"first_name":"Reedik","last_name":"Magi","full_name":"Magi, Reedik"},{"last_name":"Visscher","full_name":"Visscher, Peter M","first_name":"Peter M"},{"full_name":"Ronnegard, Lars","last_name":"Ronnegard","first_name":"Lars"},{"id":"E5D42276-F5DA-11E9-8E24-6303E6697425","first_name":"Matthew Richard","last_name":"Robinson","orcid":"0000-0001-8982-8813","full_name":"Robinson, Matthew Richard"}],"external_id":{"isi":["000724450600023"]},"article_processing_charge":"No","title":"Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits","acknowledgement":"This project was funded by an SNSF Eccellenza Grant to MRR (PCEGP3-181181), and by core funding from the Institute of Science and Technology Austria. We would like to thank the participants of the cohort studies, and the Ecole Polytechnique Federal Lausanne (EPFL) SCITAS for their excellent compute resources, their generosity with their time and the kindness of their support. P.M.V. acknowledges funding from the Australian National Health and Medical Research Council (1113400) and the Australian Research Council (FL180100072). L.R. acknowledges funding from the Kjell & Märta Beijer Foundation (Stockholm, Sweden). We also would like to acknowledge Simone Rubinacci, Oliver Delanau, Alexander Terenin, Eleonora Porcu, and Mike Goddard for their useful comments and suggestions.","quality_controlled":"1","publisher":"Springer Nature","oa":1,"has_accepted_license":"1","isi":1,"year":"2021","day":"30","publication":"Nature Communications","doi":"10.1038/s41467-021-27258-9","date_published":"2021-11-30T00:00:00Z","date_created":"2020-09-17T10:52:38Z"},{"month":"05","scopus_import":"1","main_file_link":[{"url":"https://arxiv.org/abs/2005.07637","open_access":"1"}],"oa_version":"Preprint","abstract":[{"lang":"eng","text":"Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner?\r\nTo address this question, we define the batch dynamic CONGEST model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labelled graph under batch changes. We investigate, when a batch of alpha edge label changes arrive, - how much time as a function of alpha we need to update an existing solution, and - how much information the nodes have to keep in local memory between batches in order to update the solution quickly.\r\nOur work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. The diverse time complexity of our model spans from constant time, through time polynomial in alpha, and to alpha time, which we show to be enough for any task."}],"related_material":{"record":[{"status":"public","id":"10855","relation":"extended_version"}]},"ec_funded":1,"language":[{"iso":"eng"}],"publication_identifier":{"isbn":["9781450380720"]},"publication_status":"published","status":"public","type":"conference","conference":{"start_date":"2021-06-14","location":"Virtual, Online","end_date":"2021-06-18","name":"SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems"},"_id":"10854","department":[{"_id":"DaAl"}],"date_updated":"2023-09-26T10:40:55Z","quality_controlled":"1","publisher":"Association for Computing Machinery","oa":1,"acknowledgement":"We thank Jukka Suomela for discussions. We also thank our shepherd Mohammad Hajiesmaili and the reviewers for their time and suggestions on how to improve the paper. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska–Curie grant agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N.","date_published":"2021-05-01T00:00:00Z","doi":"10.1145/3410220.3453923","date_created":"2022-03-18T08:48:41Z","page":"71-72","day":"01","publication":"Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","year":"2021","project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning","grant_number":"805223"},{"call_identifier":"H2020","_id":"26A5D39A-B435-11E9-9278-68D0E5697425","name":"Coordination in constrained and natural distributed systems","grant_number":"840605"}],"title":"Input-dynamic distributed algorithms for communication networks","author":[{"full_name":"Foerster, Klaus-Tycho","last_name":"Foerster","first_name":"Klaus-Tycho"},{"full_name":"Korhonen, Janne","last_name":"Korhonen","first_name":"Janne","id":"C5402D42-15BC-11E9-A202-CA2BE6697425"},{"first_name":"Ami","last_name":"Paz","full_name":"Paz, Ami"},{"full_name":"Rybicki, Joel","orcid":"0000-0002-6432-6646","last_name":"Rybicki","id":"334EFD2E-F248-11E8-B48F-1D18A9856A87","first_name":"Joel"},{"first_name":"Stefan","full_name":"Schmid, Stefan","last_name":"Schmid"}],"article_processing_charge":"No","external_id":{"arxiv":["2005.07637"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication Networks.” Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp. 71–72, doi:10.1145/3410220.3453923.","ieee":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.","short":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, in:, Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp. 71–72.","apa":"Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems (pp. 71–72). Virtual, Online: Association for Computing Machinery. https://doi.org/10.1145/3410220.3453923","ama":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. In: Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery; 2021:71-72. doi:10.1145/3410220.3453923","chicago":"Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 71–72. Association for Computing Machinery, 2021. https://doi.org/10.1145/3410220.3453923.","ista":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic distributed algorithms for communication networks. Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems, 71–72."}},{"department":[{"_id":"DaAl"}],"date_updated":"2023-09-26T10:40:55Z","status":"public","keyword":["Computer Networks and Communications","Hardware and Architecture","Safety","Risk","Reliability and Quality","Computer Science (miscellaneous)"],"article_type":"original","type":"journal_article","_id":"10855","volume":5,"issue":"1","related_material":{"record":[{"relation":"shorter_version","status":"public","id":"10854"}]},"ec_funded":1,"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2476-1249"]},"publication_status":"published","month":"03","intvolume":" 5","scopus_import":"1","main_file_link":[{"url":"https://arxiv.org/abs/2005.07637","open_access":"1"}],"oa_version":"Preprint","abstract":[{"text":"Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner? To address this question, we define the batch dynamic \\congest model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labeled graph under batch changes. We investigate, when a batch of α edge label changes arrive, \\beginitemize \\item how much time as a function of α we need to update an existing solution, and \\item how much information the nodes have to keep in local memory between batches in order to update the solution quickly. \\enditemize Our work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. In particular, we derive non-trivial upper bounds for two selected, contrasting problems: maintaining a minimum spanning tree and detecting cliques.","lang":"eng"}],"title":"Input-dynamic distributed algorithms for communication networks","author":[{"last_name":"Foerster","full_name":"Foerster, Klaus-Tycho","first_name":"Klaus-Tycho"},{"id":"C5402D42-15BC-11E9-A202-CA2BE6697425","first_name":"Janne","full_name":"Korhonen, Janne","last_name":"Korhonen"},{"full_name":"Paz, Ami","last_name":"Paz","first_name":"Ami"},{"orcid":"0000-0002-6432-6646","full_name":"Rybicki, Joel","last_name":"Rybicki","first_name":"Joel","id":"334EFD2E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Stefan","last_name":"Schmid","full_name":"Schmid, Stefan"}],"article_processing_charge":"No","external_id":{"arxiv":["2005.07637"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"chicago":"Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery, 2021. https://doi.org/10.1145/3447384.","ista":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 5(1), 1–33.","mla":"Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1, Association for Computing Machinery, 2021, pp. 1–33, doi:10.1145/3447384.","ieee":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.","short":"K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, Proceedings of the ACM on Measurement and Analysis of Computing Systems 5 (2021) 1–33.","apa":"Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3447384","ama":"Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 2021;5(1):1-33. doi:10.1145/3447384"},"project":[{"grant_number":"840605","name":"Coordination in constrained and natural distributed systems","call_identifier":"H2020","_id":"26A5D39A-B435-11E9-9278-68D0E5697425"},{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning"}],"doi":"10.1145/3447384","date_published":"2021-03-01T00:00:00Z","date_created":"2022-03-18T09:10:27Z","page":"1-33","day":"01","publication":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","year":"2021","quality_controlled":"1","publisher":"Association for Computing Machinery","oa":1,"acknowledgement":"We thank Jukka Suomela for discussions. We also thank our shepherd Mohammad Hajiesmaili\r\nand the reviewers for their time and suggestions on how to improve the paper. This project\r\nhas received funding from the European Research Council (ERC) under the European Union’s\r\nHorizon 2020 research and innovation programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research and innovation programme under the Marie\r\nSk lodowska–Curie grant agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N."},{"article_number":"103499","title":"Algorithms and conditional lower bounds for planning problems","author":[{"last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Dvořák, Wolfgang","last_name":"Dvořák","first_name":"Wolfgang"},{"first_name":"Monika H","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","orcid":"0000-0002-5008-6530","full_name":"Henzinger, Monika H","last_name":"Henzinger"},{"first_name":"Alexander","full_name":"Svozil, Alexander","last_name":"Svozil"}],"external_id":{"arxiv":["1804.07031"],"isi":["000657537500003"]},"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Chatterjee K, Dvořák W, Henzinger MH, Svozil A. 2021. Algorithms and conditional lower bounds for planning problems. Artificial Intelligence. 297(8), 103499.","chicago":"Chatterjee, Krishnendu, Wolfgang Dvořák, Monika H Henzinger, and Alexander Svozil. “Algorithms and Conditional Lower Bounds for Planning Problems.” Artificial Intelligence. Elsevier, 2021. https://doi.org/10.1016/j.artint.2021.103499.","short":"K. Chatterjee, W. Dvořák, M.H. Henzinger, A. Svozil, Artificial Intelligence 297 (2021).","ieee":"K. Chatterjee, W. Dvořák, M. H. Henzinger, and A. Svozil, “Algorithms and conditional lower bounds for planning problems,” Artificial Intelligence, vol. 297, no. 8. Elsevier, 2021.","ama":"Chatterjee K, Dvořák W, Henzinger MH, Svozil A. Algorithms and conditional lower bounds for planning problems. Artificial Intelligence. 2021;297(8). doi:10.1016/j.artint.2021.103499","apa":"Chatterjee, K., Dvořák, W., Henzinger, M. H., & Svozil, A. (2021). Algorithms and conditional lower bounds for planning problems. Artificial Intelligence. Elsevier. https://doi.org/10.1016/j.artint.2021.103499","mla":"Chatterjee, Krishnendu, et al. “Algorithms and Conditional Lower Bounds for Planning Problems.” Artificial Intelligence, vol. 297, no. 8, 103499, Elsevier, 2021, doi:10.1016/j.artint.2021.103499."},"publisher":"Elsevier","quality_controlled":"1","oa":1,"doi":"10.1016/j.artint.2021.103499","date_published":"2021-03-16T00:00:00Z","date_created":"2021-03-28T22:01:40Z","day":"16","publication":"Artificial Intelligence","isi":1,"year":"2021","status":"public","article_type":"original","type":"journal_article","_id":"9293","department":[{"_id":"KrCh"}],"date_updated":"2023-09-26T10:41:42Z","month":"03","intvolume":" 297","scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1804.07031"}],"oa_version":"Preprint","abstract":[{"text":"We consider planning problems for graphs, Markov Decision Processes (MDPs), and games on graphs in an explicit state space. While graphs represent the most basic planning model, MDPs represent interaction with nature and games on graphs represent interaction with an adversarial environment. We consider two planning problems with k different target sets: (a) the coverage problem asks whether there is a plan for each individual target set; and (b) the sequential target reachability problem asks whether the targets can be reached in a given sequence. For the coverage problem, we present a linear-time algorithm for graphs, and quadratic conditional lower bound for MDPs and games on graphs. For the sequential target problem, we present a linear-time algorithm for graphs, a sub-quadratic algorithm for MDPs, and a quadratic conditional lower bound for games on graphs. Our results with conditional lower bounds, based on the boolean matrix multiplication (BMM) conjecture and strong exponential time hypothesis (SETH), establish (i) model-separation results showing that for the coverage problem MDPs and games on graphs are harder than graphs, and for the sequential reachability problem games on graphs are harder than MDPs and graphs; and (ii) problem-separation results showing that for MDPs the coverage problem is harder than the sequential target problem.","lang":"eng"}],"issue":"8","volume":297,"related_material":{"record":[{"status":"public","id":"35","relation":"earlier_version"}]},"language":[{"iso":"eng"}],"publication_identifier":{"issn":["0004-3702"]},"publication_status":"published"},{"_id":"13063","status":"public","tmp":{"image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)"},"type":"research_data_reference","ddc":["570"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-09-26T10:36:15Z","citation":{"ista":"Robinson MR. 2021. Probabilistic inference of the genetic architecture of functional enrichment of complex traits, Dryad, 10.5061/dryad.sqv9s4n51.","chicago":"Robinson, Matthew Richard. “Probabilistic Inference of the Genetic Architecture of Functional Enrichment of Complex Traits.” Dryad, 2021. https://doi.org/10.5061/dryad.sqv9s4n51.","apa":"Robinson, M. R. (2021). Probabilistic inference of the genetic architecture of functional enrichment of complex traits. Dryad. https://doi.org/10.5061/dryad.sqv9s4n51","ama":"Robinson MR. Probabilistic inference of the genetic architecture of functional enrichment of complex traits. 2021. doi:10.5061/dryad.sqv9s4n51","ieee":"M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.","short":"M.R. Robinson, (2021).","mla":"Robinson, Matthew Richard. Probabilistic Inference of the Genetic Architecture of Functional Enrichment of Complex Traits. Dryad, 2021, doi:10.5061/dryad.sqv9s4n51."},"department":[{"_id":"MaRo"}],"title":"Probabilistic inference of the genetic architecture of functional enrichment of complex traits","article_processing_charge":"No","author":[{"id":"E5D42276-F5DA-11E9-8E24-6303E6697425","first_name":"Matthew Richard","full_name":"Robinson, Matthew Richard","orcid":"0000-0001-8982-8813","last_name":"Robinson"}],"oa_version":"Published Version","abstract":[{"lang":"eng","text":"We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only $\\leq$ 10\\% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having >95% probability of contributing >0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data."}],"month":"11","main_file_link":[{"url":"https://doi.org/10.5061/dryad.sqv9s4n51","open_access":"1"}],"oa":1,"publisher":"Dryad","day":"04","year":"2021","license":"https://creativecommons.org/publicdomain/zero/1.0/","date_created":"2023-05-23T16:20:16Z","date_published":"2021-11-04T00:00:00Z","related_material":{"record":[{"id":"8429","status":"public","relation":"used_in_publication"}],"link":[{"url":"https://github.com/medical-genomics-group/gmrm","relation":"software"}]},"doi":"10.5061/dryad.sqv9s4n51"},{"oa_version":"Submitted Version","abstract":[{"lang":"eng","text":"The high processing cost, poor mechanical properties and moderate performance of Bi2Te3–based alloys used in thermoelectric devices limit the cost-effectiveness of this energy conversion technology. Towards solving these current challenges, in the present work, we detail a low temperature solution-based approach to produce Bi2Te3-Cu2-xTe nanocomposites with improved thermoelectric performance. Our approach consists in combining proper ratios of colloidal nanoparticles and to consolidate the resulting mixture into nanocomposites using a hot press. The transport properties of the nanocomposites are characterized and compared with those of pure Bi2Te3 nanomaterials obtained following the same procedure. In contrast with most previous works, the presence of Cu2-xTe nanodomains does not result in a significant reduction of the lattice thermal conductivity of the reference Bi2Te3 nanomaterial, which is already very low. However, the introduction of Cu2-xTe yields a nearly threefold increase of the power factor associated to a simultaneous increase of the Seebeck coefficient and electrical conductivity at temperatures above 400 K. Taking into account the band alignment of the two materials, we rationalize this increase by considering that Cu2-xTe nanostructures, with a relatively low electron affinity, are able to inject electrons into Bi2Te3, enhancing in this way its electrical conductivity. The simultaneous increase of the Seebeck coefficient is related to the energy filtering of charge carriers at energy barriers within Bi2Te3 domains associated with the accumulation of electrons in regions nearby a Cu2-xTe/Bi2Te3 heterojunction. Overall, with the incorporation of a proper amount of Cu2-xTe nanoparticles, we demonstrate a 250% improvement of the thermoelectric figure of merit of Bi2Te3."}],"intvolume":" 418","month":"08","main_file_link":[{"url":"https://ddd.uab.cat/record/271949","open_access":"1"}],"scopus_import":"1","language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"issn":["1385-8947"]},"ec_funded":1,"issue":"8","volume":418,"_id":"9304","status":"public","type":"journal_article","article_type":"original","date_updated":"2023-09-27T07:36:29Z","department":[{"_id":"MaIb"}],"acknowledgement":"This work was supported by the European Regional Development Funds and by the Generalitat de Catalunya through the project 2017SGR1246. Y.Z, C.X, M.L, K.X and X.H thank the China Scholarship Council for the scholarship support. MI acknowledges financial support from IST Austria. YL acknowledges funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 754411. ICN2\r\nacknowledges funding from Generalitat de Catalunya 2017 SGR 327 and the Spanish MINECO project ENE2017-85087-C3. ICN2 is supported by the Severo Ochoa program from the Spanish MINECO (grant no. SEV-2017-0706) and is funded by the CERCA Program/Generalitat de Catalunya. Part of the present work has been performed in the framework of Universitat Autònoma de Barcelona Materials Science PhD program.","oa":1,"publisher":"Elsevier","quality_controlled":"1","publication":"Chemical Engineering Journal","day":"15","year":"2021","isi":1,"date_created":"2021-04-04T22:01:20Z","date_published":"2021-08-15T00:00:00Z","doi":"10.1016/j.cej.2021.129374","article_number":"129374","project":[{"_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"short":"Y. Zhang, C. Xing, Y. Liu, M. Li, K. Xiao, P. Guardia, S. Lee, X. Han, A. Moghaddam, J.J. Roa, J. Arbiol, M. Ibáñez, K. Pan, M. Prato, Y. Xie, A. Cabot, Chemical Engineering Journal 418 (2021).","ieee":"Y. Zhang et al., “Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride,” Chemical Engineering Journal, vol. 418, no. 8. Elsevier, 2021.","apa":"Zhang, Y., Xing, C., Liu, Y., Li, M., Xiao, K., Guardia, P., … Cabot, A. (2021). Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride. Chemical Engineering Journal. Elsevier. https://doi.org/10.1016/j.cej.2021.129374","ama":"Zhang Y, Xing C, Liu Y, et al. Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride. Chemical Engineering Journal. 2021;418(8). doi:10.1016/j.cej.2021.129374","mla":"Zhang, Yu, et al. “Influence of Copper Telluride Nanodomains on the Transport Properties of N-Type Bismuth Telluride.” Chemical Engineering Journal, vol. 418, no. 8, 129374, Elsevier, 2021, doi:10.1016/j.cej.2021.129374.","ista":"Zhang Y, Xing C, Liu Y, Li M, Xiao K, Guardia P, Lee S, Han X, Moghaddam A, Roa JJ, Arbiol J, Ibáñez M, Pan K, Prato M, Xie Y, Cabot A. 2021. Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride. Chemical Engineering Journal. 418(8), 129374.","chicago":"Zhang, Yu, Congcong Xing, Yu Liu, Mengyao Li, Ke Xiao, Pablo Guardia, Seungho Lee, et al. “Influence of Copper Telluride Nanodomains on the Transport Properties of N-Type Bismuth Telluride.” Chemical Engineering Journal. Elsevier, 2021. https://doi.org/10.1016/j.cej.2021.129374."},"title":"Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride","article_processing_charge":"No","external_id":{"isi":["000655672000005"]},"author":[{"first_name":"Yu","full_name":"Zhang, Yu","last_name":"Zhang"},{"last_name":"Xing","full_name":"Xing, Congcong","first_name":"Congcong"},{"last_name":"Liu","orcid":"0000-0001-7313-6740","full_name":"Liu, Yu","id":"2A70014E-F248-11E8-B48F-1D18A9856A87","first_name":"Yu"},{"full_name":"Li, Mengyao","last_name":"Li","first_name":"Mengyao"},{"full_name":"Xiao, Ke","last_name":"Xiao","first_name":"Ke"},{"full_name":"Guardia, Pablo","last_name":"Guardia","first_name":"Pablo"},{"id":"BB243B88-D767-11E9-B658-BC13E6697425","first_name":"Seungho","full_name":"Lee, Seungho","orcid":"0000-0002-6962-8598","last_name":"Lee"},{"full_name":"Han, Xu","last_name":"Han","first_name":"Xu"},{"first_name":"Ahmad","full_name":"Moghaddam, Ahmad","last_name":"Moghaddam"},{"full_name":"Roa, Joan J","last_name":"Roa","first_name":"Joan J"},{"full_name":"Arbiol, Jordi","last_name":"Arbiol","first_name":"Jordi"},{"full_name":"Ibáñez, Maria","orcid":"0000-0001-5013-2843","last_name":"Ibáñez","first_name":"Maria","id":"43C61214-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Kai","full_name":"Pan, Kai","last_name":"Pan"},{"last_name":"Prato","full_name":"Prato, Mirko","first_name":"Mirko"},{"last_name":"Xie","full_name":"Xie, Ying","first_name":"Ying"},{"last_name":"Cabot","full_name":"Cabot, Andreu","first_name":"Andreu"}]},{"date_updated":"2023-09-27T07:46:09Z","department":[{"_id":"SiHi"}],"_id":"9793","article_type":"original","type":"journal_article","status":"public","publication_identifier":{"issn":["0896-6273"],"eissn":["1097-4199"]},"publication_status":"published","language":[{"iso":"eng"}],"issue":"15","volume":109,"ec_funded":1,"abstract":[{"text":"Astrocytes extensively infiltrate the neuropil to regulate critical aspects of synaptic development and function. This process is regulated by transcellular interactions between astrocytes and neurons via cell adhesion molecules. How astrocytes coordinate developmental processes among one another to parse out the synaptic neuropil and form non-overlapping territories is unknown. Here we identify a molecular mechanism regulating astrocyte-astrocyte interactions during development to coordinate astrocyte morphogenesis and gap junction coupling. We show that hepaCAM, a disease-linked, astrocyte-enriched cell adhesion molecule, regulates astrocyte competition for territory and morphological complexity in the developing mouse cortex. Furthermore, conditional deletion of Hepacam from developing astrocytes significantly impairs gap junction coupling between astrocytes and disrupts the balance between synaptic excitation and inhibition. Mutations in HEPACAM cause megalencephalic leukoencephalopathy with subcortical cysts in humans. Therefore, our findings suggest that disruption of astrocyte self-organization mechanisms could be an underlying cause of neural pathology.","lang":"eng"}],"oa_version":"Published Version","pmid":1,"scopus_import":"1","main_file_link":[{"url":"https://doi.org/10.1016/j.neuron.2021.05.025","open_access":"1"}],"month":"08","intvolume":" 109","citation":{"ama":"Baldwin KT, Tan CX, Strader ST, et al. HepaCAM controls astrocyte self-organization and coupling. Neuron. 2021;109(15):2427-2442.e10. doi:10.1016/j.neuron.2021.05.025","apa":"Baldwin, K. T., Tan, C. X., Strader, S. T., Jiang, C., Savage, J. T., Elorza-Vidal, X., … Eroglu, C. (2021). HepaCAM controls astrocyte self-organization and coupling. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2021.05.025","ieee":"K. T. Baldwin et al., “HepaCAM controls astrocyte self-organization and coupling,” Neuron, vol. 109, no. 15. Elsevier, p. 2427–2442.e10, 2021.","short":"K.T. Baldwin, C.X. Tan, S.T. Strader, C. Jiang, J.T. Savage, X. Elorza-Vidal, X. Contreras, T. Rülicke, S. Hippenmeyer, R. Estévez, R.-R. Ji, C. Eroglu, Neuron 109 (2021) 2427–2442.e10.","mla":"Baldwin, Katherine T., et al. “HepaCAM Controls Astrocyte Self-Organization and Coupling.” Neuron, vol. 109, no. 15, Elsevier, 2021, p. 2427–2442.e10, doi:10.1016/j.neuron.2021.05.025.","ista":"Baldwin KT, Tan CX, Strader ST, Jiang C, Savage JT, Elorza-Vidal X, Contreras X, Rülicke T, Hippenmeyer S, Estévez R, Ji R-R, Eroglu C. 2021. HepaCAM controls astrocyte self-organization and coupling. Neuron. 109(15), 2427–2442.e10.","chicago":"Baldwin, Katherine T., Christabel X. Tan, Samuel T. Strader, Changyu Jiang, Justin T. Savage, Xabier Elorza-Vidal, Ximena Contreras, et al. “HepaCAM Controls Astrocyte Self-Organization and Coupling.” Neuron. Elsevier, 2021. https://doi.org/10.1016/j.neuron.2021.05.025."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Katherine T.","full_name":"Baldwin, Katherine T.","last_name":"Baldwin"},{"full_name":"Tan, Christabel X.","last_name":"Tan","first_name":"Christabel X."},{"first_name":"Samuel T.","full_name":"Strader, Samuel T.","last_name":"Strader"},{"first_name":"Changyu","last_name":"Jiang","full_name":"Jiang, Changyu"},{"first_name":"Justin T.","last_name":"Savage","full_name":"Savage, Justin T."},{"full_name":"Elorza-Vidal, Xabier","last_name":"Elorza-Vidal","first_name":"Xabier"},{"id":"475990FE-F248-11E8-B48F-1D18A9856A87","first_name":"Ximena","full_name":"Contreras, Ximena","last_name":"Contreras"},{"first_name":"Thomas","full_name":"Rülicke, Thomas","last_name":"Rülicke"},{"id":"37B36620-F248-11E8-B48F-1D18A9856A87","first_name":"Simon","full_name":"Hippenmeyer, Simon","orcid":"0000-0003-2279-1061","last_name":"Hippenmeyer"},{"last_name":"Estévez","full_name":"Estévez, Raúl","first_name":"Raúl"},{"first_name":"Ru-Rong","full_name":"Ji, Ru-Rong","last_name":"Ji"},{"first_name":"Cagla","full_name":"Eroglu, Cagla","last_name":"Eroglu"}],"external_id":{"pmid":["34171291"],"isi":["000692851900010"]},"article_processing_charge":"No","title":"HepaCAM controls astrocyte self-organization and coupling","project":[{"name":"Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development","grant_number":"725780","call_identifier":"H2020","_id":"260018B0-B435-11E9-9278-68D0E5697425"}],"isi":1,"year":"2021","day":"04","publication":"Neuron","page":"2427-2442.e10","doi":"10.1016/j.neuron.2021.05.025","date_published":"2021-08-04T00:00:00Z","date_created":"2021-08-06T09:08:25Z","acknowledgement":"This work was supported by the National Institutes of Health (R01 DA047258 and R01 NS102237 to C.E., F32 NS100392 to K.T.B.) and the Holland-Trice Brain Research Award (to C.E.). K.T.B. was supported by postdoctoral fellowships from the Foerster-Bernstein Family and The Hartwell Foundation. The Hippenmeyer lab was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovations program (725780 LinPro) to S.H. R.E. was supported by Ministerio de Ciencia y Tecnología (RTI2018-093493-B-I00). We thank the Duke Light Microscopy Core Facility, the Duke Transgenic Mouse Facility, Dr. U. Schulte for assistance with proteomic experiments, and Dr. D. Silver for critical review of the manuscript. Cartoon elements of figure panels were created using BioRender.com.","publisher":"Elsevier","quality_controlled":"1","oa":1}]