Eshaan Nichani

According to our database, Eshaan Nichani authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How Transformers Learn Causal Structure with Gradient Descent.

Eshaan Nichani, Alex Damian, Jason D. Lee

CoRR, 2024

2023

Learning Hierarchical Polynomials with Three-Layer Neural Networks.

Zihao Wang, Eshaan Nichani, Jason D. Lee

CoRR, 2023

Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks.

Eshaan Nichani, Alex Damian, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fine-Tuning Language Models with Just Forward Passes.

Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models.

Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability.

Alex Damian, Eshaan Nichani, Jason D. Lee

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials.

Eshaan Nichani, Yu Bai, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors.

Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2020

Do Deeper Convolutional Networks Perform Better?

Eshaan Nichani, Adityanarayanan Radhakrishnan, Caroline Uhler

CoRR, 2020

Balancedness and Alignment are Unlikely in Linear Neural Networks.

Adityanarayanan Radhakrishnan, Eshaan Nichani, Daniel Irving Bernstein, Caroline Uhler

CoRR, 2020