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4840 Publications

2022 | Submitted | Preprint | IST-REx-ID: 14601 | OA
D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2022 | Research Data Reference | IST-REx-ID: 13064 | OA
E. Orliac et al., “Improving genome-wide association discovery and genomic prediction accuracy in biobank data.” Dryad, 2022.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2022 | Research Data Reference | IST-REx-ID: 13066 | OA
E. Koch, M. Ravinet, A. M. Westram, K. Jonannesson, and R. Butlin, “Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution.” Dryad, 2022.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2022 | Research Data Reference | IST-REx-ID: 13076 | OA
A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “Multi-queues can be state-of-the-art priority schedulers.” Zenodo, 2022.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2022 | Published | Conference Paper | IST-REx-ID: 13239 | OA
T. L. Van Der Plas, T. P. Vogels, and S. G. Manohar, “Predictive learning enables neural networks to learn complex working memory tasks,” in Proceedings of Machine Learning Research, 2022, vol. 199, pp. 518–531.
[Published Version] View | Files available
 
2022 | Published | Journal Article | IST-REx-ID: 13240 | OA
K. D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, and A. Djamei, “Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis,” Frontiers in Fungal Biology, vol. 3. Frontiers Media, 2022.
[Published Version] View | Files available | DOI
 
2022 | Published | Conference Paper | IST-REx-ID: 13241 | OA
N. H. Konstantinov and C. Lampert, “On the impossibility of fairness-aware learning from corrupted data,” in Proceedings of Machine Learning Research, 2022, vol. 171, pp. 59–83.
[Preprint] View | Files available | 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 | 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: 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: 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: 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: 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: 14173 | OA
F. Wenzel et al., “Assaying out-of-distribution generalization in transfer learning,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2022, vol. 35, pp. 7181–7198.
[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 | 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: 14216 | OA
A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, and F. Locatello, “ASIF: Coupled data turns unimodal models to multimodal without training,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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