Peruzzo, Matilda. “Geometric Superinductors and Their Applications in Circuit Quantum Electrodynamics.”https://doi.org/10.15479/at:ista:9920__Institute of Science and Technology Austria, 2021.https://doi.org/10.15479/at:ista:9920 .
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DOI: 10.15479/at:ista:9920

Nadiradze, Giorgi, Ilia Markov, Bapi Chatterjee, Vyacheslav  Kungurtsev, and Dan-Adrian Alistarh. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:9037–45, 2021.
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arXiv: 2001.05918

Kamath Hosdurg, Chethan, Karen Klein, Krzysztof Z Pietrzak, and Daniel Wichs. “Limits on the Adaptive Security of Yao’s Garbling.”https://doi.org/10.1007/978-3-030-84245-1_17__In 41st Annual International Cryptology Conference, Part II , 12826:486–515. Cham: Springer Nature, 2021.https://doi.org/10.1007/978-3-030-84245-1_17 .
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DOI: 10.1007/978-3-030-84245-1_17

Klein, Karen, Guillermo Pascual Perez, Michael Walter, Chethan Kamath Hosdurg, Margarita Capretto, Miguel Cueto Noval, Ilia Markov, Michelle X Yeo, Joel F Alwen, and Krzysztof Z Pietrzak. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.”https://doi.org/10.1109/sp40001.2021.00035__In 2021 IEEE Symposium on Security and Privacy , 268–84. IEEE, 2021.https://doi.org/10.1109/sp40001.2021.00035 .
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Kamath Hosdurg, Chethan, Karen Klein, and Krzysztof Z Pietrzak. “On Treewidth, Separators and Yao’s Garbling.” In 19th Theory of Cryptography Conference 2021. International Association for Cryptologic Research, 2021.
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Piankov, Anton. “Towards Designer Materials Using Customizable Particle Shape.”https://doi.org/10.15479/at:ista:10422__Institute of Science and Technology Austria, 2021.https://doi.org/10.15479/at:ista:10422 .
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Konstantinov, Nikola H, and Christoph Lampert. “Fairness through Regularization for Learning to Rank.”https://doi.org/10.48550/arXiv.2102.05996__ArXiv, n.d.https://doi.org/10.48550/arXiv.2102.05996 .
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arXiv: 2102.05996

Rzadkowski, Wojciech, Mikhail Lemeshko, and Johan H. Mentink. “Artificial Neural Network States for Non-Additive Systems.”https://doi.org/10.48550/arXiv.2105.15193__ArXiv, n.d.https://doi.org/10.48550/arXiv.2105.15193 .
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arXiv: 2105.15193

Phuong, Mary. “Underspecification in Deep Learning.”https://doi.org/10.15479/AT:ISTA:9418__Institute of Science and Technology Austria, 2021.https://doi.org/10.15479/AT:ISTA:9418 .
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Träuble, Frederik, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, and Stefan Bauer. “On Disentangled Representations Learned from Correlated Data.” In Proceedings of the 38th International Conference on Machine Learning, 139:10401–12. ML Research Press, 2021.
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arXiv: 2006.07886

Yèche, Hugo, Gideon Dresdner, Francesco Locatello, Matthias Hüser, and Gunnar Rätsch. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” In Proceedings of 38th International Conference on Machine Learning, 139:11964–74. ML Research Press, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/14176
arXiv: 2106.05142

Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” In 35th Conference on Neural Information Processing Systems, 34:116–28, 2021.
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arXiv: 2107.01057

Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.”https://doi.org/10.24963/ijcai.2021/322__In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2337–43. International Joint Conferences on Artificial Intelligence, 2021.https://doi.org/10.24963/ijcai.2021/322 .
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arXiv: 2105.09240

Kügelgen, Julius von, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, and Francesco Locatello. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” In Advances in Neural Information Processing Systems, 34:16451–67, 2021.
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arXiv: 2106.04619

Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural Interpreters.” In Advances in Neural Information Processing Systems, 34:10985–98, 2021.
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arXiv: 2110.06399

Scholkopf, Bernhard, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio. “Toward Causal Representation Learning.”https://doi.org/10.1109/jproc.2021.3058954__Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 2021.https://doi.org/10.1109/jproc.2021.3058954 .
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arXiv: 2102.11107

Dittadi, Andrea, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, and Bernhard Schölkopf. “On the Transfer of Disentangled Representations in Realistic Settings.” In The Ninth International Conference on Learning Representations, 2021.
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arXiv: 2010.14407

Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.”https://doi.org/10.48550/arXiv.2111.13693__ArXiv, n.d.https://doi.org/10.48550/arXiv.2111.13693 .
LibreCat: https://research-explorer.ista.ac.at/record/14221
DOI: 10.48550/arXiv.2111.13693
arXiv: 2111.13693

Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” In ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/14332

Koval, Illya. “Local Strong Birkhoff Conjecture and Local Spectral Rigidity of Almost Every Ellipse.”https://doi.org/10.48550/ARXIV.2111.12171__ArXiv, n.d.https://doi.org/10.48550/ARXIV.2111.12171 .
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DOI: 10.48550/ARXIV.2111.12171
arXiv: 2111.12171