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Kragl, Bernhard, Shaz Qadeer, and Thomas A Henzinger. “Refinement for Structured Concurrent Programs.”https://doi.org/10.1007/978-3-030-53288-8_14__In Computer Aided Verification, 12224:275–98. Springer Nature, 2020.https://doi.org/10.1007/978-3-030-53288-8_14 .
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Kragl, Bernhard, Constantin Enea, Thomas A Henzinger, Suha Orhun Mutluergil, and Shaz Qadeer. “Inductive Sequentialization of Asynchronous Programs.”https://doi.org/10.1145/3385412.3385980__In Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation, 227–42. Association for Computing Machinery, 2020.https://doi.org/10.1145/3385412.3385980 .
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Dos Santos Caldas, Paulo R. “Organization and Dynamics of Treadmilling Filaments in Cytoskeletal Networks of FtsZ and Its Crosslinkers.”https://doi.org/10.15479/AT:ISTA:8358__Institute of Science and Technology Austria, 2020.https://doi.org/10.15479/AT:ISTA:8358 .
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Fischer, Julian L, and Sebastian Hensel. “Weak–Strong Uniqueness for the Navier–Stokes Equation for Two Fluids with Surface Tension.”https://doi.org/10.1007/s00205-019-01486-2__Archive for Rational Mechanics and Analysis. Springer Nature, 2020.https://doi.org/10.1007/s00205-019-01486-2 .
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Fischer, Julian L, Sebastian Hensel, Tim Laux, and Thilo Simon. “The Local Structure of the Energy Landscape in Multiphase Mean Curvature Flow: Weak-Strong Uniqueness and Stability of Evolutions.” ArXiv, n.d.
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arXiv: 2003.05478

Peruzzo, Matilda, Andrea Trioni, Farid Hassani, Martin Zemlicka, and Johannes M Fink. “Surpassing the Resistance Quantum with a Geometric Superinductor.”https://doi.org/10.1103/PhysRevApplied.14.044055__Physical Review Applied. American Physical Society, 2020.https://doi.org/10.1103/PhysRevApplied.14.044055 .
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Gladbach, Peter, Eva Kopfer, Jan Maas, and Lorenzo Portinale. “Homogenisation of One-Dimensional Discrete Optimal Transport.”https://doi.org/10.1016/j.matpur.2020.02.008__Journal de Mathematiques Pures et Appliquees. Elsevier, 2020.https://doi.org/10.1016/j.matpur.2020.02.008 .
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Forkert, Dominik L, Jan Maas, and Lorenzo Portinale. “Evolutionary -Convergence of Entropic Gradient Flow Structures for Fokker-Planck Equations in Multiple Dimensions.” ArXiv, n.d.
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Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” In Proceedings of the 37th International Conference on Machine Learning, 119:5416–25. ML Research Press, 2020.
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Rzadkowski, Wojciech, N Defenu, S Chiacchiera, A Trombettoni, and Giacomo Bighin. “Detecting Composite Orders in Layered Models via Machine Learning.”https://doi.org/10.1088/1367-2630/abae44__New Journal of Physics. IOP Publishing, 2020.https://doi.org/10.1088/1367-2630/abae44 .
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Mysliwy, Krzysztof, and Robert Seiringer. “Microscopic Derivation of the Fröhlich Hamiltonian for the Bose Polaron in the Mean-Field Limit.”https://doi.org/10.1007/s00023-020-00969-3__Annales Henri Poincare. Springer Nature, 2020.https://doi.org/10.1007/s00023-020-00969-3 .
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arXiv: 2003.12371

Stark, Stefan G, Joanna Ficek, Francesco Locatello, Ximena Bonilla, Stéphane Chevrier, Franziska Singer, Rudolf Aebersold, et al. “SCIM: Universal Single-Cell Matching with Unpaired Feature Sets.”https://doi.org/10.1093/bioinformatics/btaa843__Bioinformatics. Oxford University Press, 2020.https://doi.org/10.1093/bioinformatics/btaa843 .
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Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Commentary on the Unsupervised Learning of Disentangled Representations.”https://doi.org/10.1609/aaai.v34i09.7120__In The 34th AAAI Conference on Artificial Intelligence, 34:13681–84. Association for the Advancement of Artificial Intelligence, 2020.https://doi.org/10.1609/aaai.v34i09.7120 .
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arXiv: 2007.14184

Locatello, Francesco, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, and Michael Tschannen. “Weakly-Supervised Disentanglement without Compromises.” In Proceedings of the 37th International Conference on Machine Learning, 119:6348–6359, 2020.
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Négiar, Geoffrey, Gideon Dresdner, Alicia Tsai, Laurent El Ghaoui, Francesco Locatello, Robert M. Freund, and Fabian Pedregosa. “Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization.” In Proceedings of the 37th International Conference on Machine Learning, 119:7253–62, 2020.
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arXiv: 2002.11860

Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Sober Look at the Unsupervised Learning of Disentangled Representations and Their Evaluation.” Journal of Machine Learning Research. MIT Press, 2020.
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