Loss Landscapes of Regularized Linear Autoencoders. - Daniel Kunin; Jonathan M. Bloom; Aleksandrina Goeva; Cotton Seed (ICML, 2019)

Two Routes to Scalable Credit Assignment without Weight Symmetry. - Daniel Kunin; Aran Nayebi; Javier Sagastuy-Breña; Surya Ganguli; Jonathan M. Bloom; Daniel Yamins (ICML, 2020)

Pruning neural networks without any data by iteratively conserving synaptic flow. - Hidenori Tanaka; Daniel Kunin; Daniel L. K. Yamins; Surya Ganguli (NeurIPS, 2020)

Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. - Daniel Kunin; Javier Sagastuy-Breña; Surya Ganguli; Daniel L. K. Yamins; Hidenori Tanaka (ICLR, 2021)

Noether's Learning Dynamics: Role of Symmetry Breaking in Neural Networks. - Hidenori Tanaka; Daniel Kunin (NeurIPS, 2021)

Noether's Learning Dynamics: The Role of Kinetic Symmetry Breaking in Deep Learning. - Hidenori Tanaka; Daniel Kunin (CoRR, 2021)

Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion. - Daniel Kunin; Javier Sagastuy-Breña; Lauren E. Gillespie; Eshed Margalit; Hidenori Tanaka; Surya Ganguli; Daniel L. K. Yamins (CoRR, 2021)

The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks. - Daniel Kunin; Atsushi Yamamura; Chao Ma; Surya Ganguli (ICLR, 2023)

Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks. - Feng Chen 046; Daniel Kunin; Atsushi Yamamura; Surya Ganguli (NeurIPS, 2023)

Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. - Daniel Kunin; Allan Raventós; Clémentine C. J. Dominé; Feng Chen 046; David A. Klindt; Andrew M. Saxe; Surya Ganguli (NeurIPS, 2024)

The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. - Daniel Kunin; Javier Sagastuy-Breña; Lauren E. Gillespie; Eshed Margalit; Hidenori Tanaka; Surya Ganguli; Daniel L. K. Yamins (Neural Comput., 2024)

From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks. - Clémentine Carla Juliette Dominé; Nicolas Anguita; Alexandra M. Proca; Lukas Braun; Daniel Kunin; Pedro A. M. Mediano; Andrew M. Saxe (ICLR, 2025)

Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks. - Daniel Kunin; Giovanni Luca Marchetti; Feng Chen; Dhruva Karkada; James B. Simon; Michael Robert DeWeese; Surya Ganguli; Nina Miolane (CoRR, 2025)