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11357 Publications
2024 |
Published |
Conference Paper |
IST-REx-ID: 18971 |
Arefin, R., Zhang, Y., Baratin, A., Locatello, F., Rish, I., Liu, D., & Kawaguchi, K. (2024). Unsupervised concept discovery mitigates spurious correlations. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 1672–1688). Vienna, Austria: ML Research Press.
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| arXiv
2024 |
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Conference Paper |
IST-REx-ID: 18972 |
Bombari, S., & Mondelli, M. (2024). How spurious features are memorized: Precise analysis for random and NTK features. In 41st International Conference on Machine Learning (Vol. 235, pp. 4267–4299). Vienna, Austria: ML Research Press.
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| arXiv
2024 |
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Conference Paper |
IST-REx-ID: 18973 |
Bombari, S., & Mondelli, M. (2024). Towards understanding the word sensitivity of attention layers: A study via random features. In 41st International Conference on Machine Learning (Vol. 235, pp. 4300–4328). Vienna, Austria: ML Research Press.
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| arXiv
2024 |
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Conference Paper |
IST-REx-ID: 18974 |
Svoboda, J., Bansal, S., & Chatterjee, K. (2024). Reinforcement learning from reachability specifications: PAC guarantees with expected conditional distance. In 41st International Conference on Machine Learning (Vol. 235, pp. 47331–47344). Vienna, Austria: ML Research Press.
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2024 |
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Conference Paper |
IST-REx-ID: 18975 |
Modoranu, I.-V., Kalinov, A., Kurtic, E., Frantar, E., & Alistarh, D.-A. (2024). Error feedback can accurately compress preconditioners. In 41st International Conference on Machine Learning (Vol. 235, pp. 35910–35933). Vienna, Austria: ML Research Press.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18976 |
Islamov, R., Safaryan, M., & Alistarh, D.-A. (2024). AsGrad: A sharp unified analysis of asynchronous-SGD algorithms. In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 649–657). Valencia, Spain: ML Research Press.
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| arXiv
2024 |
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Conference Paper |
IST-REx-ID: 18977 |
Dettmers, T., Svirschevski, R. A., Egiazarian, V., Kuznedelev, D., Frantar, E., Ashkboos, S., … Alistarh, D.-A. (2024). SpQR: A sparse-quantized representation for near-lossless LLM weight compression. In 12th International Conference on Learning Representations. Vienna, Austria: OpenReview.
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| arXiv
2024 |
Draft |
Preprint |
IST-REx-ID: 18981 |
Brown, A., & Draganov, O. (n.d.). Discrete microlocal Morse theory. arXiv. https://doi.org/10.48550/arXiv.2209.14993
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18996 |
Chen, T., Bello, K., Locatello, F., Aragam, B., & Ravikumar, P. K. (2024). Identifying general mechanism shifts in linear causal representations. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18998 |
Draganov, O., & Skiena, S. (2024). The shape of word embeddings: Quantifying non-isometry with topological data analysis. In Findings of the Association for Computational Linguistics: EMNLP 2024 (pp. 12080–12099). Miami, FL, United States: Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.705
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| arXiv
2024 |
Submitted |
Preprint |
IST-REx-ID: 18999 |
Cultrera di Montesano, S., Draganov, O., Edelsbrunner, H., & Saghafian, M. (n.d.). Chromatic topological data analysis. arXiv. https://doi.org/10.48550/ARXIV.2406.04102
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 19005 |
Yao, D., Muller, C. J., & Locatello, F. (2024). Marrying causal representation learning with dynamical systems for science. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 19007 |
Kori, A., Locatello, F., Santhirasekaram, A., Toni, F., Glocker, B., & De Sousa Ribeiro, F. (2024). Identifiable object-centric representation learning via probabilistic slot attention. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
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| arXiv
2024 |
Draft |
Preprint |
IST-REx-ID: 19013 |
Glas, J., & Hase-Liu, M. (n.d.). Terminal singularities of the moduli space of curves on low degree hypersurfaces and the circle method. arXiv. https://doi.org/10.48550/arXiv.2412.14923
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 19028 |
Sakai, H., Freude, C., Auzinger, T., Hahn, D., & Wimmer, M. (2024). A statistical approach to Monte Carlo denoising. In Proceedings - SIGGRAPH Asia 2024 Conference Papers. Tokyo, Japan: Association for Computing Machinery. https://doi.org/10.1145/3680528.3687591
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| WoS
2024 |
Published |
Journal Article |
IST-REx-ID: 19051 |
Browning, T. D. (2024). The polynomial sieve and equal sums of like polynomials. International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rnae066
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| WoS
2024 |
Published |
Preprint |
IST-REx-ID: 19063 |
Zverev, E., Abdelnabi, S., Tabesh, S., Fritz, M., & Lampert, C. (2024). Can LLMs separate instructions from data? And what do we even mean by that? arXiv. https://doi.org/10.48550/arXiv.2403.06833
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| arXiv
2024 |
Research Data Reference |
IST-REx-ID: 19307 |
Hwong, Y.-L., & Muller, C. J. (2024). Data - The unreasonable efficiency of total rain evaporation removal in triggering convective self-aggregation. Zenodo. https://doi.org/10.5281/ZENODO.10687169
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2024 |
Published |
Journal Article |
IST-REx-ID: 19408 |
Verwimp, E., Aljundi, R., Ben-David, S., Bethge, M., Cossu, A., Gepperth, A., … Van De Ven, G. M. (2024). Continual learning: Applications and the road forward. Transactions on Machine Learning Research. Transactions on Machine Learning Research.
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| arXiv
2024 |
Draft |
Preprint |
IST-REx-ID: 19425 |
Karle, V., Lemeshko, M., Bouhon, A., Slager, R.-J., & Ünal, F. N. (n.d.). Anomalous multi-gap topological phases in periodically driven quantum rotors. arXiv. https://doi.org/10.48550/arXiv.2408.16848
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| arXiv