Sam Buchanan

23 papers A* 7Misc 1Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Beyond Scores: Proximal Diffusion Models.
CoRR
Zhenghan Fang, Mateo Díaz, Sam Buchanan, Jeremias Sulam
2025 J jnl
End-to-End Test-Time Training for Long Context.
CoRR
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
2025 J jnl
On the Edge of Memorization in Diffusion Models.
CoRR
Sam Buchanan, Druv Pai, Yi Ma, Valentin De Bortoli
2024 — conf
Emergence of Segmentation with Minimalistic White-Box Transformers.
CPAL
Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma
2024 A* conf
Masked Completion via Structured Diffusion with White-Box Transformers.
ICLR
Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma
2024 J jnl
Masked Completion via Structured Diffusion with White-Box Transformers.
CoRR
Druv Pai, Ziyang Wu, Sam Buchanan, Yaodong Yu, Yi Ma
2024 A* conf
What's in a Prior? Learned Proximal Networks for Inverse Problems.
ICLR
Zhenghan Fang, Sam Buchanan, Jeremias Sulam
2024 J jnl
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?
J. Mach. Learn. Res.
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma
2023 A* conf
Canonical Factors for Hybrid Neural Fields.
ICCV
Brent Yi, Weijia Zeng, Sam Buchanan, Yi Ma
2023 J jnl
Canonical Factors for Hybrid Neural Fields.
CoRR
Brent Yi, Weijia Zeng, Sam Buchanan, Yi Ma
2023 J jnl
Emergence of Segmentation with Minimalistic White-Box Transformers.
CoRR
Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma
2023 J jnl
What's in a Prior? Learned Proximal Networks for Inverse Problems.
CoRR
Zhenghan Fang, Sam Buchanan, Jeremias Sulam
2023 A* conf
White-Box Transformers via Sparse Rate Reduction.
NeurIPS
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma
2023 J jnl
White-Box Transformers via Sparse Rate Reduction.
CoRR
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma
2023 J jnl
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?
CoRR
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma
2022 — —
Deep Networks Through the Lens of Low-Dimensional Structure: Towards Mathematical and Computational Principles for Nonlinear Data
Sam Buchanan
2022 J jnl
Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization.
CoRR
Sam Buchanan, Jingkai Yan, Ellie Haber, John Wright
2021 A* conf
Deep Networks Provably Classify Data on Curves.
NeurIPS
Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright
2021 J jnl
Deep Networks Provably Classify Data on Curves.
CoRR
Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright
2021 A* conf
Deep Networks and the Multiple Manifold Problem.
ICLR
Sam Buchanan, Dar Gilboa, John Wright
2020 J jnl
Deep Networks and the Multiple Manifold Problem.
CoRR
Sam Buchanan, Dar Gilboa, John Wright
2019 A* conf
Efficient Dictionary Learning with Gradient Descent.
ICML
Dar Gilboa, Sam Buchanan, John Wright
2018 Misc conf
Efficient Model-Free Learning to Overcome Hardware Nonidealities in Analog-to-Information Converters.
ICASSP
Sam Buchanan, Tanbir Haque, Peter R. Kinget, John Wright