Publications

• E. Collins-Woodfin, I. Seroussi, B. García Malaxechebarría, A. W Mackenzie, E. Paquette, C. Paquette “The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms” arXiv:2405.19585 (2024) (NeurIPS  2024)

• N. Rubin, Z. Ringel, I. Seroussi, Moritz Helias “A Unified Approach to Feature Learning in Bayesian Neural Networks” High-dimensional Learning Dynamics 2024: The Emergence of Structure and Reasoning (ICML 2024) DOI

• I. Seroussi, A. Miron, Z. Ringel, “Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks” Machine Learning: Science and Technology 5.3 (2024): 035048 arXiv

• X. Wang, I. Seroussi, F. Lu, “Minimax Convergence Rate of Learning Interaction Kernels”, arXiv preprint arXiv:2311.16852 (2023) arXiv

• N. Rubin, I. Seroussi, Z. Ringel, “Grokking as a First Order Phase Transition in Two Layer Networks” arXiv preprint arXiv:2310.03789 (2023) arXiv, ICLR 2024

• E. Collins-Woodfin, C. Paquette, E. Paquette, and I. Seroussi. “Hitting the high-dimensional notes: An ode for SGD learning dynamics on GLMs and multi-index models.” Information and Inference: A Journal of the IMA, 13(4):iaae028, 2024, arXiv

• I. Seroussi, AA. Alemi, M. Helias, Z. Ringel “Speed Limit for Deep Learning” arXiv preprint arXiv:2307.14653 (2023) arXiv

• I. Seroussi, G. Naveh, Z. Ringel, “Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs.” Nature Communications, 14(1), p.908 (2023) DOI, arXiv

• I. Seroussi, O. Zeitouni, “Lower Bounds on the Generalization Error of Nonlinear Learning Models” IEEE Transactions on Information Theory (2022) DOI, arXiv

• C. Cosco, I. Seroussi, O. Zeitouni, “Directed polymers on infinite graphs”. Communications in Mathematical Physics, 1-38 (2021).DOI, arXiv

• I. Seroussi, N. Sochen, “Localization Phase Transition in Stochastic Dynamics on Networks with Hub Topology.” Physica A: Statistical Mechanics and its Applications (2020): 124636, DOI

• I. Seroussi, N. Levy, D. Paolotti, N. Sochen, E. Yom-Tov, “Revealing the Dynamics of Influenza Strains in Europe Using a Data-Quality Sensitive Lagrangian Framework” arXiv

• I. Seroussi, N. Levy, E. Yom-Tov, “Multi-Season Analysis Reveals the Spatial Structure of Disease Spread” Physica A: Statistical Mechanics and its Applications (2020): 124425 DOI, arXiv

• I. Seroussi, N. Sochen, “Spectral Analysis of a Non-Equilibrium Stochastic Dynamics on a General Network”, Scientific Reports 8 (1), 14333 DOI

• D. Anaby, D. Morozov, I. Seroussi, S. Hametner, N. Sochen, Y. Cohen, “Axon Diameter Distribution Mapping in Fixed Spinal Cord from Single and Double Diffusion Encoding MRI”, NMR in Biomedicine 32 (12), e4170e, DOI

• I. Seroussi, D. S. Grebenkov, O. Pasternak, N. Sochen, “Microscopic Interpretation and Generalization of the Bloch-Torrey Equations for Diffusion MR”, Journal of Magnetic Resonance 277 (2017): 95-103, DOI

• I. Seroussi, E. Berg, Y. Oreg, “Topological Superconducting Phases of Weakly Coupled Quantum Wires”, Physical Review B 89, (2014) 104523, DOI

• I. Seroussi, D. Veikherman, N. Ofer, S. Yehudai-resheff, K. Keren, “Segmentation and Tracking of Live cells in Phase‐Contrast images Using Directional Gradient Vector Flow for Snakes”, Journal of Microscopy 247.2 (2012): 137-146, DOI.