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Zietlow, Dominik, et al. “Leveling down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers.”10.1109/cvpr52688.2022.01016__2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 10400–11, doi:10.1109/cvpr52688.2022.01016.
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Rahaman, Nasim, et al. “Neural Attentive Circuits.” 36th Conference on Neural Information Processing Systems, vol. 35, 2022.
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Dittadi, Andrea, et al. “Generalization and Robustness Implications in Object-Centric Learning.” Proceedings of the 39th International Conference on Machine Learning, vol. 2022, ML Research Press, pp. 5221–85.
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Schott, Lukas, et al. “Visual Representation Learning Does Not Generalize Strongly within the  Same Domain.” 10th International Conference on Learning Representations, 2022.
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Yao, Jian, et al. “Self-Supervised Amodal Video Object Segmentation.”10.48550/arXiv.2210.12733__36th Conference on Neural Information Processing Systems, 2022, doi:10.48550/arXiv.2210.12733.
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Rolland, Paul, et al. “Score Matching Enables Causal Discovery of Nonlinear Additive Noise  Models.” Proceedings of the 39th International Conference on Machine Learning, vol. 162, ML Research Press, 2022, pp. 18741–53.
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Dittadi, Andrea, et al. “The Role of Pretrained Representations for the OOD Generalization of  Reinforcement Learning Agents.” 10th International Conference on Learning Representations, 2022.
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Makansi, Osama, et al. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” 10th International Conference on Learning Representations, 2022.
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Mambelli, Davide, et al. “Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.”10.48550/arXiv.2201.13388__ArXiv, 2201.13388, doi:10.48550/arXiv.2201.13388.
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Rahaman, Nasim, et al. “A General Purpose Neural Architecture for Geospatial Systems.” 36th Conference on Neural Information Processing Systems.
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Brighi, Pietro, et al. “Hilbert Space Fragmentation and Slow Dynamics in Particle-Conserving Quantum East Models.”10.48550/arXiv.2210.15607__ArXiv, 2210.15607, doi:10.48550/arXiv.2210.15607.
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Boegershausen, Nina, et al. “WAR and SAR: Two TRNA Synthetases Implicated in Autosomal Recessive Microcephaly.”10.1002/humu.24430__Human Mutation, vol. 43, no. 10, Wiley, 2022, pp. 1454–71, doi:10.1002/humu.24430.
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Cali, Elisa, et al. “A Homozygous ME C-Terminal Variant Causes a Lethal Neurodegenerative Disease.”10.1016/j.gim.2022.07.013__Genetics in Medicine, vol. 24, no. 10, Elsevier, 2022, pp. 2194–203, doi:10.1016/j.gim.2022.07.013.
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Lin, Sheng-Jia, et al. “Biallelic Variants in WAR Cause a Highly Variable Neurodevelopmental Syndrome and Implicate a Critical Exon for Normal Auditory Function.”10.1002/humu.24435__Human Mutation, vol. 43, no. 10, Wiley, 2022, pp. 1472–89, doi:10.1002/humu.24435.
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Arroyo Guevara, Alan M., and Stefan Felsner. “Approximating the Bundled Crossing Number.”10.1007/978-3-030-96731-4_31__WALCOM 2022: Algorithms and Computation, vol. 13174, Springer Nature, 2022, pp. 383–95, doi:10.1007/978-3-030-96731-4_31.
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Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.”10.4230/LIPIcs.CONCUR.2022.11__33rd International Conference on Concurrency Theory , vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.CONCUR.2022.11.
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Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.”10.1609/aaai.v36i6.20631__Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 6, Association for the Advancement of Artificial Intelligence, 2022, pp. 6755–64, doi:10.1609/aaai.v36i6.20631.
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Konstantinov, Nikola H., and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research, vol. 23, ML Research Press, 2022, pp. 1–60.
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Konstantinov, Nikola H., and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” Proceedings of Machine Learning Research, vol. 171, ML Research Press, 2022, pp. 59–83.
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