Sam Buchanan

According to our database, Sam Buchanan authored at least 15 papers between 2018 and 2025.

Collaborative distances:

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

2025

End-to-End Test-Time Training for Long Context.

Arnuv Tandon, Karan Dalal, Xinhao Li, Daniel Koceja, Marcel Rød, Sam Buchanan, Xiaolong Wang, Jure Leskovec, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin, Jed McCaleb, Yejin Choi, Yu Sun

CoRR, December, 2025

On the Edge of Memorization in Diffusion Models.

Sam Buchanan, Druv Pai, Yi Ma, Valentin De Bortoli

CoRR, August, 2025

Beyond Scores: Proximal Diffusion Models.

Zhenghan Fang, Mateo Díaz, Sam Buchanan, Jeremias Sulam

CoRR, July, 2025

2024

White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?

Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma

J. Mach. Learn. Res., 2024

Masked Completion via Structured Diffusion with White-Box Transformers.

Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

What's in a Prior? Learned Proximal Networks for Inverse Problems.

Zhenghan Fang, Sam Buchanan, Jeremias Sulam

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Emergence of Segmentation with Minimalistic White-Box Transformers.

Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma

Proceedings of the Conference on Parsimony and Learning, 2024

2023

White-Box Transformers via Sparse Rate Reduction.

Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma

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

Canonical Factors for Hybrid Neural Fields.

Brent Yi, Weijia Zeng, Sam Buchanan, Yi Ma

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Deep Networks Through the Lens of Low-Dimensional Structure: Towards Mathematical and Computational Principles for Nonlinear Data

Sam Buchanan

PhD thesis, 2022

Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization.

Sam Buchanan, Jingkai Yan, Ellie Haber, John Wright

CoRR, 2022

2021

Deep Networks Provably Classify Data on Curves.

Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Networks and the Multiple Manifold Problem.

Sam Buchanan, Dar Gilboa, John Wright

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Efficient Dictionary Learning with Gradient Descent.

Dar Gilboa, Sam Buchanan, John Wright

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Efficient Model-Free Learning to Overcome Hardware Nonidealities in Analog-to-Information Converters.

Sam Buchanan, Tanbir Haque, Peter R. Kinget, John Wright

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018