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Sidak Pal Singh

Empirical Inference Collaborator

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I am doing my PhD in the CLS program, advised by Thomas Hofmann at ETH and Bernhard Schölkopf at MPI. My research focuses on the theory of deep neural networks --- in particular, understanding inherent structural properties due to the nature of parameterization and its effects on generalization.

In my free time, I like to read (philosophy, literature), hike as well as saunter, sing & play badminton. 

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Empirical Inference Conference Paper The Directionality of Optimization Trajectories in Neural Networks Singh, S. P., He, B., Hofmann, T., Schölkopf, B. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) URL BibTeX
Empirical Inference Conference Paper What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis Ormaniec, W., Dangel, F., Singh, S. P. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX
Empirical Inference Conference Paper Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks Zhao*, J., Singh*, S. P., Lucchi, A. Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 37:114965-115000, (Editors: A. Globerson and L. Mackey and D. Belgrave and A. Fan and U. Paquet and J. Tomczak and C. Zhang), Curran Associates, Inc., 38th Annual Conference on Neural Information Processing Systems, December 2024, *equal contribution (Published) URL BibTeX
Empirical Inference Conference Paper Some Intriguing Aspects about Lipschitz Continuity of Neural Networks Khromov*, G., Singh*, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Conference Paper Towards Meta-Pruning via Optimal Transport Theus, A., Geimer, O., Wicke, F., Hofmann, T., Anagnostidis, S., Singh, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX
Empirical Inference Conference Paper Transformer Fusion with Optimal Transport Imfeld*, M., Graldi*, J., Giordano*, M., Hofmann, T., Anagnostidis, S., Singh, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX
Empirical Inference Conference Paper The Hessian perspective into the Nature of Convolutional Neural Networks Singh, S. P., Hofmann, T., Schölkopf, B. Proceedings of the 40th International Conference on Machine Learning (ICML), 202:31930-31968, Proceedings of Machine Learning Research, (Editors: A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato and J. Scarlett), PMLR, July 2023 (Published) URL BibTeX
Empirical Inference Conference Paper Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse Noci*, L., Sotiris*, A., Biggio*, L., Orvieto*, A., Singh*, S. P., Lucchi, A. Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 35:27198-27211, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Annual Conference on Neural Information Processing Systems, December 2022, *equal contribution (Published) arXiv URL BibTeX
Empirical Inference Conference Paper Phenomenology of Double Descent in Finite-Width Neural Networks Singh, S. P., Lucchi, A., Hofmann, T., Schölkopf, B. The Tenth International Conference on Learning Representations (ICLR 2022), International Conference on Learning Representations, April 2022 (Published) URL BibTeX
Empirical Inference Conference Paper Analytic Insights into Structure and Rank of Neural Network Hessian Maps Singh, S. P., Bachmann, G., Hofmann, T. Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 23914-23927, (Editors: M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan), Curran Associates, Inc., 35th Annual Conference on Neural Information Processing Systems, December 2021 (Published) URL BibTeX
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