Schwab, David J.

19 publications

ICLR 2026 Entropic Confinement and Mode Connectivity in Overparameterized Neural Networks Luca Di Carlo, Chase Goddard, David J. Schwab

NeurIPS 2025 Generalization vs Specialization Under Concept Shift Alex Nguyen, David J. Schwab, Vudtiwat Ngampruetikorn

ICML 2025 When Can In-Context Learning Generalize Out of Task Distribution? Chase Goddard, Lindsay M. Smith, Vudtiwat Ngampruetikorn, David J. Schwab

NeurIPSW 2024 Generalization vs Specialization Under Concept Shift Alex Nguyen, David J. Schwab, Vudtiwat Ngampruetikorn

NeurIPSW 2024 Model Recycling: Model Component Reuse to Promote In-Context Learning Lindsay M. Smith, Chase Goddard, Vudtiwat Ngampruetikorn, David J. Schwab

NeurIPSW 2024 Specialization-Generalization Transition in Exemplar-Based In-Context Learning Chase Goddard, Lindsay M. Smith, Vudtiwat Ngampruetikorn, David J. Schwab

ICLRW 2023 AWE: Adaptive Weight-Space Ensembling for Few-Shot Fine-Tuning Jean-Christophe Gagnon-Audet, Ricardo Pio Monti, David J. Schwab

ICLR 2023 Don’t Forget the Nullspace! Nullspace Occupancy as a Mechanism for Out of Distribution Failure Daksh Idnani, Vivek Madan, Naman Goyal, David J. Schwab, Shanmukha Ramakrishna Vedantam

ICMLW 2023 Understanding Energy-Based Modeling of Proteins via an Empirically Motivated Minimal Ground Truth Model Peter William Fields, Vudtiwat Ngampruetikorn, Rama Ranganathan, David J. Schwab, Stephanie Palmer

NeurIPS 2022 Information Bottleneck Theory of High-Dimensional Regression: Relevancy, Efficiency and Optimality Vudtiwat Ngampruetikorn, David J Schwab

NeurIPS 2021 An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers Ramakrishna Vedantam, David Lopez-Paz, David J Schwab

NeurIPSW 2021 Learning Background Invariance Improves Generalization and Robustness in Self-Supervised Learning on ImageNet and Beyond Chaitanya Ryali, David J. Schwab, Ari S. Morcos

NeurIPS 2021 Perturbation Theory for the Information Bottleneck Vudtiwat Ngampruetikorn, David J Schwab

ICLR 2021 Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs Jonathan Frankle, David J. Schwab, Ari S. Morcos

NeurIPS 2020 Learning Optimal Representations with the Decodable Information Bottleneck Yann Dubois, Douwe Kiela, David J Schwab, Ramakrishna Vedantam

ICLR 2020 The Early Phase of Neural Network Training Jonathan Frankle, David J. Schwab, Ari S. Morcos

NeurIPS 2018 Learning to Share and Hide Intentions Using Information Regularization Dj Strouse, Max Kleiman-Weiner, Josh Tenenbaum, Matt Botvinick, David J Schwab

NeurIPS 2016 Supervised Learning with Tensor Networks Edwin Stoudenmire, David J Schwab

UAI 2016 The Deterministic Information Bottleneck Dj Strouse, David J. Schwab