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114 Publications
2023 | Conference Paper | IST-REx-ID: 13053 | 
E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, and D.-A. Alistarh, “CrAM: A Compression-Aware Minimizer,” in 11th International Conference on Learning Representations , Kigali, Rwanda .
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| arXiv
2023 | Thesis | IST-REx-ID: 13074 |
E.-A. Peste, “Efficiency and generalization of sparse neural networks,” Institute of Science and Technology Austria, 2023.
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2023 | Journal Article | IST-REx-ID: 14320 |
P. M. Henderson, A. Ghazaryan, A. A. Zibrov, A. F. Young, and M. Serbyn, “Deep learning extraction of band structure parameters from density of states: A case study on trilayer graphene,” Physical Review B, vol. 108, no. 12. American Physical Society, 2023.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14410
P. Tomaszewska and C. Lampert, “On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift,” in International Workshop on Reproducible Research in Pattern Recognition, Montreal, Canada, 2023, vol. 14068, pp. 67–73.
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2023 | Journal Article | IST-REx-ID: 14446 |
J. Jakubík, M. Phuong, M. Chvosteková, and A. Krakovská, “Against the flow of time with multi-output models,” Measurement Science Review, vol. 23, no. 4. Sciendo, pp. 175–183, 2023.
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2023 | Conference Paper | IST-REx-ID: 14771 |
E. B. Iofinova, E.-A. Peste, and D.-A. Alistarh, “Bias in pruned vision models: In-depth analysis and countermeasures,” in 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, 2023, pp. 24364–24373.
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| WoS
| arXiv
2023 | Conference Paper | IST-REx-ID: 14921 |
P. Súkeník, M. Mondelli, and C. Lampert, “Deep neural collapse is provably optimal for the deep unconstrained features model,” in 37th Annual Conference on Neural Information Processing Systems, New Orleans, LA, United States.
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| arXiv
2023 | Preprint | IST-REx-ID: 15039 |
B. Prach and C. Lampert, “1-Lipschitz neural networks are more expressive with N-activations,” arXiv. .
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| arXiv
2022 | Preprint | IST-REx-ID: 12660 |
J. A. Scott, M. X. Yeo, and C. Lampert, “Cross-client Label Propagation for transductive federated learning,” arXiv. .
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| arXiv
2022 | Preprint | IST-REx-ID: 12662 |
P. Súkeník and C. Lampert, “Generalization in Multi-objective machine learning,” arXiv. .
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| arXiv