Critical initialization of wide and deep neural networks through partial Jacobians: general theory and applications to LayerNorm. - Darshil Doshi; Tianyu He; Andrey Gromov (CoRR, 2021)

AutoInit: Automatic Initialization via Jacobian Tuning. - Tianyu He; Darshil Doshi; Andrey Gromov (CoRR, 2022)

Critical Initialization of Wide and Deep Neural Networks using Partial Jacobians: General Theory and Applications. - Darshil Doshi; Tianyu He; Andrey Gromov (NeurIPS, 2023)

To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets. - Darshil Doshi; Aritra Das; Tianyu He; Andrey Gromov (ICLR, 2024)

Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks. - Tianyu He; Darshil Doshi; Aritra Das; Andrey Gromov (NeurIPS, 2024)

Grokking Modular Polynomials. - Darshil Doshi; Tianyu He; Aritra Das; Andrey Gromov (CoRR, 2024)

(How) Can Transformers Predict Pseudo-Random Numbers? - Tao Tao; Darshil Doshi; Dayal Singh Kalra; Tianyu He; Maissam Barkeshli (CoRR, 2025)