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114 Publications
2021 | Preprint | IST-REx-ID: 10803 | 
Konstantinov, N. H., & Lampert, C. (n.d.). Fairness through regularization for learning to rank. arXiv. https://doi.org/10.48550/arXiv.2102.05996
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2021 | Thesis | IST-REx-ID: 9418 |
Phuong, M. (2021). Underspecification in deep learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9418
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2021 | Book Chapter | IST-REx-ID: 14987
Lampert, C. (2021). Zero-Shot Learning. In K. Ikeuchi (Ed.), Computer Vision (2nd ed., pp. 1395–1397). Cham: Springer. https://doi.org/10.1007/978-3-030-63416-2_874
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2020 | Preprint | IST-REx-ID: 8063 |
Anciukevicius, T., Lampert, C., & Henderson, P. M. (n.d.). Object-centric image generation with factored depths, locations, and appearances. arXiv.
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2020 | Conference Paper | IST-REx-ID: 8188 |
Henderson, P. M., & Lampert, C. (2020). Unsupervised object-centric video generation and decomposition in 3D. In 34th Conference on Neural Information Processing Systems (Vol. 33, pp. 3106–3117). Vancouver, Canada: Curran Associates.
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2020 | Journal Article | IST-REx-ID: 6952 |
Henderson, P. M., & Ferrari, V. (2020). Learning single-image 3D reconstruction by generative modelling of shape, pose and shading. International Journal of Computer Vision. Springer Nature. https://doi.org/10.1007/s11263-019-01219-8
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2020 | Conference Paper | IST-REx-ID: 7936 |
Royer, A., & Lampert, C. (2020). Localizing grouped instances for efficient detection in low-resource scenarios. In IEEE Winter Conference on Applications of Computer Vision. Snowmass Village, CO, United States: IEEE. https://doi.org/10.1109/WACV45572.2020.9093288
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2020 | Conference Paper | IST-REx-ID: 7937 |
Royer, A., & Lampert, C. (2020). A flexible selection scheme for minimum-effort transfer learning. In 2020 IEEE Winter Conference on Applications of Computer Vision. Snowmass Village, CO, United States: IEEE. https://doi.org/10.1109/WACV45572.2020.9093635
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2020 | Book Chapter | IST-REx-ID: 8092 |
Royer, A., Bousmalis, K., Gouws, S., Bertsch, F., Mosseri, I., Cole, F., & Murphy, K. (2020). XGAN: Unsupervised image-to-image translation for many-to-many mappings. In R. Singh, M. Vatsa, V. M. Patel, & N. Ratha (Eds.), Domain Adaptation for Visual Understanding (pp. 33–49). Springer Nature. https://doi.org/10.1007/978-3-030-30671-7_3
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2020 | Conference Paper | IST-REx-ID: 7481 |
Phuong, M., & Lampert, C. (2020). Functional vs. parametric equivalence of ReLU networks. In 8th International Conference on Learning Representations. Online.
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2020 | Conference Paper | IST-REx-ID: 8724 |
Konstantinov, N. H., Frantar, E., Alistarh, D.-A., & Lampert, C. (2020). On the sample complexity of adversarial multi-source PAC learning. In Proceedings of the 37th International Conference on Machine Learning (Vol. 119, pp. 5416–5425). Online: ML Research Press.
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2020 | Thesis | IST-REx-ID: 8390 |
Royer, A. (2020). Leveraging structure in Computer Vision tasks for flexible Deep Learning models. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8390
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2020 | Conference Paper | IST-REx-ID: 8186 |
Henderson, P. M., Tsiminaki, V., & Lampert, C. (2020). Leveraging 2D data to learn textured 3D mesh generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 7498–7507). Virtual: IEEE. https://doi.org/10.1109/CVPR42600.2020.00752
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2020 | Journal Article | IST-REx-ID: 6944 |
Sun, R., & Lampert, C. (2020). KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications. International Journal of Computer Vision. Springer Nature. https://doi.org/10.1007/s11263-019-01232-x
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2019 | Book (Editor) | IST-REx-ID: 7171
Kersting, K., Lampert, C., & Rothkopf, C. (Eds.). (2019). Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt (1st ed.). Wiesbaden: Springer Nature. https://doi.org/10.1007/978-3-658-26763-6
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2019 | Conference Paper | IST-REx-ID: 6942 |
Ashok, P., Brázdil, T., Chatterjee, K., Křetínský, J., Lampert, C., & Toman, V. (2019). Strategy representation by decision trees with linear classifiers. In 16th International Conference on Quantitative Evaluation of Systems (Vol. 11785, pp. 109–128). Glasgow, United Kingdom: Springer Nature. https://doi.org/10.1007/978-3-030-30281-8_7
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2019 | Journal Article | IST-REx-ID: 6554 |
Xian, Y., Lampert, C., Schiele, B., & Akata, Z. (2019). Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tpami.2018.2857768
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2019 | Conference Paper | IST-REx-ID: 7479 |
Phuong, M., & Lampert, C. (2019). Distillation-based training for multi-exit architectures. In IEEE International Conference on Computer Vision (Vol. 2019–October, pp. 1355–1364). Seoul, Korea: IEEE. https://doi.org/10.1109/ICCV.2019.00144
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2019 | Conference Paper | IST-REx-ID: 7640 |
Kolesnikov, A., Kuznetsova, A., Lampert, C., & Ferrari, V. (2019). Detecting visual relationships using box attention. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00217
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2019 | Conference Paper | IST-REx-ID: 6569 |
Phuong, M., & Lampert, C. (2019). Towards understanding knowledge distillation. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 5142–5151). Long Beach, CA, United States: ML Research Press.
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2019 | Conference Paper | IST-REx-ID: 6590 |
Konstantinov, N. H., & Lampert, C. (2019). Robust learning from untrusted sources. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 3488–3498). Long Beach, CA, USA: ML Research Press.
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2019 | Conference Paper | IST-REx-ID: 6482 |
Sun, R., & Lampert, C. (2019). KS(conf): A light-weight test if a ConvNet operates outside of Its specifications (Vol. 11269, pp. 244–259). Presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany: Springer Nature. https://doi.org/10.1007/978-3-030-12939-2_18
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2018 | Thesis | IST-REx-ID: 68 |
Zimin, A. (2018). Learning from dependent data. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH1048
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2018 | Thesis | IST-REx-ID: 197 |
Kolesnikov, A. (2018). Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_1021
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2018 | Journal Article | IST-REx-ID: 563 |
Ringbauer, H., Kolesnikov, A., Field, D., & Barton, N. H. (2018). Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.117.300638
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2018 | Journal Article | IST-REx-ID: 321 |
Darrell, T., Lampert, C., Sebe, N., Wu, Y., & Yan, Y. (2018). Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2018.2804998
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2018 | Conference Paper | IST-REx-ID: 10882 |
Uijlings, J., Konyushkova, K., Lampert, C., & Ferrari, V. (2018). Learning intelligent dialogs for bounding box annotation. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9175–9184). Salt Lake City, UT, United States: IEEE. https://doi.org/10.1109/cvpr.2018.00956
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2018 | Conference Paper | IST-REx-ID: 6012 |
Sahoo, S., Lampert, C., & Martius, G. S. (2018). Learning equations for extrapolation and control. In Proceedings of the 35th International Conference on Machine Learning (Vol. 80, pp. 4442–4450). Stockholm, Sweden: ML Research Press.
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2018 | Conference Paper | IST-REx-ID: 6011 |
Kuzborskij, I., & Lampert, C. (2018). Data-dependent stability of stochastic gradient descent. In Proceedings of the 35 th International Conference on Machine Learning (Vol. 80, pp. 2815–2824). Stockholm, Sweden: ML Research Press.
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2018 | Conference Paper | IST-REx-ID: 6589 |
Alistarh, D.-A., Hoefler, T., Johansson, M., Konstantinov, N. H., Khirirat, S., & Renggli, C. (2018). The convergence of sparsified gradient methods. In Advances in Neural Information Processing Systems 31 (Vol. Volume 2018, pp. 5973–5983). Montreal, Canada: Neural Information Processing Systems Foundation.
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2018 | Research Data | IST-REx-ID: 5584 |
Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98
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2017 | Conference Paper | IST-REx-ID: 652
Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789
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2017 | Journal Article | IST-REx-ID: 658 |
Der, R., & Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research Foundation. https://doi.org/10.3389/fnbot.2017.00008
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2017 | Conference Paper | IST-REx-ID: 6841 |
Martius, G. S., & Lampert, C. (2017). Extrapolation and learning equations. In 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. Toulon, France: International Conference on Learning Representations.
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2017 | Conference Paper | IST-REx-ID: 750
Pielorz, J., Prandtstetter, M., Straub, M., & Lampert, C. (2017). Optimal geospatial volunteer allocation needs realistic distances. In 2017 IEEE International Conference on Big Data (pp. 3760–3763). Boston, MA, United States: IEEE. https://doi.org/10.1109/BigData.2017.8258375
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2017 | Conference Paper | IST-REx-ID: 1000 |
Kolesnikov, A., & Lampert, C. (2017). PixelCNN models with auxiliary variables for natural image modeling. In 34th International Conference on Machine Learning (Vol. 70, pp. 1905–1914). Sydney, Australia: JMLR.
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2017 | Conference Paper | IST-REx-ID: 998 |
Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL: Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.587
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2017 | Conference Paper | IST-REx-ID: 911 |
Royer, A., Kolesnikov, A., & Lampert, C. (2017). Probabilistic image colorization (p. 85.1-85.12). Presented at the BMVC: British Machine Vision Conference, London, United Kingdom: BMVA Press. https://doi.org/10.5244/c.31.85
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2017 | Conference Paper | IST-REx-ID: 1108 |
Zimin, A., & Lampert, C. (2017). Learning theory for conditional risk minimization (Vol. 54, pp. 213–222). Presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States: ML Research Press.
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2017 | Conference Paper | IST-REx-ID: 999 |
Pentina, A., & Lampert, C. (2017). Multi-task learning with labeled and unlabeled tasks (Vol. 70, pp. 2807–2816). Presented at the ICML: International Conference on Machine Learning, Sydney, Australia: ML Research Press.
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2016 | Conference Paper | IST-REx-ID: 1098 |
Pentina, A., & Urner, R. (2016). Lifelong learning with weighted majority votes (Vol. 29, pp. 3619–3627). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems.
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2016 | Conference Paper | IST-REx-ID: 1102 |
Kolesnikov, A., & Lampert, C. (2016). Improving weakly-supervised object localization by micro-annotation. In Proceedings of the British Machine Vision Conference 2016 (Vol. 2016–September, p. 92.1-92.12). York, United Kingdom: BMVA Press. https://doi.org/10.5244/C.30.92
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2016 | Conference Paper | IST-REx-ID: 1214
Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138
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2016 | Conference Paper | IST-REx-ID: 1369 |
Kolesnikov, A., & Lampert, C. (2016). Seed, expand and constrain: Three principles for weakly-supervised image segmentation (Vol. 9908, pp. 695–711). Presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands: Springer. https://doi.org/10.1007/978-3-319-46493-0_42
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2016 | Conference Paper | IST-REx-ID: 1707
Pielorz, J., & Lampert, C. (2016). Optimal geospatial allocation of volunteers for crisis management. Presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France: IEEE. https://doi.org/10.1109/ICT-DM.2015.7402041
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2016 | Conference Paper | IST-REx-ID: 8094 |
Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Self-organized control of an tendon driven arm by differential extrinsic plasticity. In Proceedings of the Artificial Life Conference 2016 (Vol. 28, pp. 142–143). Cancun, Mexico: MIT Press. https://doi.org/10.7551/978-0-262-33936-0-ch029
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2016 | Thesis | IST-REx-ID: 1126 |
Pentina, A. (2016). Theoretical foundations of multi-task lifelong learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH_776
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2015 | Conference Paper | IST-REx-ID: 1425 |
Pentina, A., & Lampert, C. (2015). Lifelong learning with non-i.i.d. tasks (Vol. 2015, pp. 1540–1548). Presented at the NIPS: Neural Information Processing Systems, Montreal, Canada: Neural Information Processing Systems.
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2015 | Journal Article | IST-REx-ID: 1533
Xia, W., Domokos, C., Xiong, J., Cheong, L., & Yan, S. (2015). Segmentation over detection via optimal sparse reconstructions. IEEE Transactions on Circuits and Systems for Video Technology. IEEE. https://doi.org/10.1109/TCSVT.2014.2379972
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2015 | Journal Article | IST-REx-ID: 1570 |
Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1508400112
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