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5034 Publications


2022 |Published| Conference Paper | IST-REx-ID: 14106 | OA
M. Lohaus, M. Kleindessner, K. Kenthapadi, F. Locatello, and C. Russell, “Are two heads the same as one? Identifying disparate treatment in fair neural networks,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2022, vol. 35, pp. 16548–16562.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14093 | OA
G. Dresdner, M.-L. Vladarean, G. Rätsch, F. Locatello, V. Cevher, and A. Yurtsever, “ Faster one-sample stochastic conditional gradient method for composite convex minimization,” in Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, Virtual, 2022, vol. 151, pp. 8439–8457.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Thesis | IST-REx-ID: 11473 | OA
K. Mysliwy, “Polarons in Bose gases and polar crystals: Some rigorous energy estimates,” Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 

2022 |Published| Journal Article | IST-REx-ID: 10564 | OA
K. Mysliwy and R. Seiringer, “Polaron models with regular interactions at strong coupling,” Journal of Statistical Physics, vol. 186, no. 1. Springer Nature, 2022.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2022 |Published| Journal Article | IST-REx-ID: 11402 | OA
K. Chatterjee and L. Doyen, “Graph planning with expected finite horizon,” Journal of Computer and System Sciences, vol. 129. Elsevier, pp. 1–21, 2022.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14114 | OA
D. Zietlow et al., “Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 10400–10411.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14168 | OA
N. Rahaman et al., “Neural attentive circuits,” in 36th Conference on Neural Information Processing Systems, New Orleans, United States, 2022, vol. 35.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Submitted| Conference Paper | IST-REx-ID: 14170 | OA
A. Dittadi, S. Papa, M. D. Vita, B. Schölkopf, O. Winther, and F. Locatello, “Generalization and robustness implications in object-centric learning,” in Proceedings of the 39th International Conference on Machine Learning, Baltimore, MD, United States, vol. 2022, pp. 5221–5285.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14172 | OA
L. Schott et al., “Visual representation learning does not generalize strongly within the  same domain,” in 10th International Conference on Learning Representations, Virtual, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14107 | OA
J. Yao et al., “Self-supervised amodal video object segmentation,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2022.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14171 | OA
P. Rolland et al., “Score matching enables causal discovery of nonlinear additive noise  models,” in Proceedings of the 39th International Conference on Machine Learning, Baltimore, MD, United States, 2022, vol. 162, pp. 18741–18753.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14174 | OA
A. Dittadi et al., “The role of pretrained representations for the OOD generalization of  reinforcement learning agents,” in 10th International Conference on Learning Representations, Virtual, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 14175 | OA
O. Makansi et al., “You mostly walk alone: Analyzing feature attribution in trajectory prediction,” in 10th International Conference on Learning Representations, Virtual, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Submitted| Preprint | IST-REx-ID: 14220 | OA
D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, and F. Locatello, “Compositional multi-object reinforcement learning with linear relation networks,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 |Submitted| Conference Paper | IST-REx-ID: 14215 | OA
N. Rahaman et al., “A general purpose neural architecture for geospatial systems,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 |Submitted| Preprint | IST-REx-ID: 12750 | OA
P. Brighi, M. Ljubotina, and M. Serbyn, “Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 11185 | OA
A. M. Arroyo Guevara and S. Felsner, “Approximating the bundled crossing number,” in WALCOM 2022: Algorithms and Computation, Jember, Indonesia, 2022, vol. 13174, pp. 383–395.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2022 |Published| Conference Paper | IST-REx-ID: 12775 | OA
K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees for reachability in uncountable Markov decision processes,” in 33rd International Conference on Concurrency Theory , Warsaw, Poland, 2022, vol. 243.
[Published Version] View | Files available | DOI | arXiv
 

2022 |Published| Journal Article | IST-REx-ID: 12510 | OA
S. A. Gruenbacher et al., “GoTube: Scalable statistical verification of continuous-depth models,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 6. Association for the Advancement of Artificial Intelligence, pp. 6755–6764, 2022.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 |Published| Journal Article | IST-REx-ID: 10802 | OA
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
[Published Version] View | Files available | arXiv
 

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