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10501 Publications


2022 | Published | Journal Article | IST-REx-ID: 13991
C. Heide et al., “Probing topological phase transitions using high-harmonic generation,” Nature Photonics, vol. 16, no. 9. Springer Nature, pp. 620–624, 2022.
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2022 | Published | Journal Article | IST-REx-ID: 13992 | OA
V. Svoboda et al., “Femtosecond photoelectron circular dichroism of chemical reactions,” Science Advances, vol. 8, no. 28. American Association for the Advancement of Science, 2022.
[Published Version] View | DOI | Download Published Version (ext.) | PubMed | Europe PMC | arXiv
 

2022 | Published | Journal Article | IST-REx-ID: 13993 | OA
X. Gong et al., “Attosecond photoionization dynamics: from molecules over clusters to the liquid phase,” Chimia, vol. 76, no. 6. Swiss Chemical Society, pp. 520–528, 2022.
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2022 | Published | Journal Article | IST-REx-ID: 13994 | OA
D. R. Baykusheva et al., “Ultrafast renormalization of the on-site Coulomb repulsion in a cuprate superconductor,” Physical Review X, vol. 12, no. 1. American Physical Society, 2022.
[Published Version] View | DOI | Download Published Version (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 | Journal Article | IST-REx-ID: 14098 | OA
Z. Keszthelyi et al., “The effects of surface fossil magnetic fields on massive star evolution: IV. Grids of models at solar, LMC, and SMC metallicities,” Monthly Notices of the Royal Astronomical Society, vol. 517, no. 2. Oxford Academic, pp. 2028–2055, 2022.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

2022 | Submitted | Preprint | IST-REx-ID: 14099 | OA
Z. Keszthelyi et al., “Spin-down and reduced mass loss in early-type stars with large-scale magnetic fields,” arXiv. .
[Submitted Version] View | DOI | Download Submitted Version (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.
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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: 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 | Preprint | IST-REx-ID: 14236 | OA
G. Goranci and M. Henzinger, “Incremental approximate maximum flow in m1/2+o(1) update time,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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