Balancedness and Alignment are Unlikely in Linear Neural Networks. - Adityanarayanan Radhakrishnan; Eshaan Nichani; Daniel Irving Bernstein; Caroline Uhler (CoRR, 2020)

Do Deeper Convolutional Networks Perform Better? - Eshaan Nichani; Adityanarayanan Radhakrishnan; Caroline Uhler (CoRR, 2020)

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors. - Chandler Squires; Annie Yun; Eshaan Nichani; Raj Agrawal; Caroline Uhler (CLeaR, 2022)

Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials. - Eshaan Nichani; Yu Bai 017; Jason D. Lee (NeurIPS, 2022)

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability. - Alex Damian; Eshaan Nichani; Jason D. Lee (ICLR, 2023)

Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models. - Alex Damian; Eshaan Nichani; Rong Ge 001; Jason D. Lee (NeurIPS, 2023)

Fine-Tuning Language Models with Just Forward Passes. - Sadhika Malladi; Tianyu Gao 001; Eshaan Nichani; Alex Damian; Jason D. Lee; Danqi Chen 001; Sanjeev Arora (NeurIPS, 2023)

Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks. - Eshaan Nichani; Alex Damian; Jason D. Lee (NeurIPS, 2023)

Learning Hierarchical Polynomials with Three-Layer Neural Networks. - Zihao Wang; Eshaan Nichani; Jason D. Lee (ICLR, 2024)

How Transformers Learn Causal Structure with Gradient Descent. - Eshaan Nichani; Alex Damian; Jason D. Lee (ICML, 2024)

Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks. - Hengyu Fu; Zihao Wang; Eshaan Nichani; Jason D. Lee (CoRR, 2024)

Learning Compositional Functions with Transformers from Easy-to-Hard Data. - Zixuan Wang; Eshaan Nichani; Alberto Bietti; Alex Damian; Daniel Hsu 001; Jason D. Lee; Denny Wu (COLT, 2025)

Learning Hierarchical Polynomials of Multiple Nonlinear Features. - Hengyu Fu; Zihao Wang; Eshaan Nichani; Jason D. Lee (ICLR, 2025)

Understanding Factual Recall in Transformers via Associative Memories. - Eshaan Nichani; Jason D. Lee; Alberto Bietti (ICLR, 2025)

Emergence and scaling laws in SGD learning of shallow neural networks. - Yunwei Ren; Eshaan Nichani; Denny Wu; Jason D. Lee (CoRR, 2025)