Independent and Decentralized Learning in Markov Potential Games. - Chinmay Maheshwari; Manxi Wu; Druv Pai; Shankar Sastry 001 (CoRR, 2022)

White-Box Transformers via Sparse Rate Reduction. - Yaodong Yu; Sam Buchanan; Druv Pai; Tianzhe Chu; Ziyang Wu; Shengbang Tong; Benjamin D. Haeffele; Yi Ma 001 (NeurIPS, 2023)

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 001 (CoRR, 2023)

Pursuit of a discriminative representation for multiple subspaces via sequential games. - Druv Pai; Michael Psenka; Chih-Yuan Chiu; Manxi Wu; Edgar Dobriban; Yi Ma 001 (J. Frankl. Inst., 2023)

Closed-Loop Transcription via Convolutional Sparse Coding. - Xili Dai; Ke Chen; Shengbang Tong; Jingyuan Zhang; Xingjian Gao; Mingyang Li; Druv Pai; Yuexiang Zhai; Xiaojun Yuan 002; Heung-Yeung Shum; Lionel M. Ni; Yi Ma 001 (CPAL, 2024)

Emergence of Segmentation with Minimalistic White-Box Transformers. - Yaodong Yu; Tianzhe Chu; Shengbang Tong; Ziyang Wu; Druv Pai; Sam Buchanan; Yi Ma 001 (CPAL, 2024)

Masked Completion via Structured Diffusion with White-Box Transformers. - Druv Pai; Sam Buchanan; Ziyang Wu; Yaodong Yu; Yi Ma 001 (ICLR, 2024)

A Global Geometric Analysis of Maximal Coding Rate Reduction. - Peng Wang 098; Huikang Liu; Druv Pai; Yaodong Yu; Zhihui Zhu; Qing Qu 001; Yi Ma 001 (ICML, 2024)

Scaling White-Box Transformers for Vision. - Jinrui Yang; Xianhang Li; Druv Pai; Yuyin Zhou; Yi Ma 001; Yaodong Yu; Cihang Xie (NeurIPS, 2024)

Congestion Pricing for Efficiency and Equity: Theory and Applications to the San Francisco Bay Area. - Chinmay Maheshwari; Kshitij Kulkarni; Druv Pai; Jiarui Yang; Manxi Wu; Shankar Sastry 001 (CoRR, 2024)

Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs. - Tianyu Guo 004; Druv Pai; Yu Bai 017; Jiantao Jiao; Michael I. Jordan; Song Mei (CoRR, 2024)

Representation Learning via Manifold Flattening and Reconstruction. - Michael Psenka; Druv Pai; Vishal Raman; Shankar Sastry 001; Yi Ma 001 (J. Mach. Learn. Res., 2024)

Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction. - Ziyang Wu; Tianjiao Ding; Yifu Lu; Druv Pai; Jingyuan Zhang; Weida Wang; Yaodong Yu; Yi Ma 001; Benjamin David Haeffele (ICLR, 2025)

Simplifying DINO via Coding Rate Regularization. - Ziyang Wu; Jingyuan Zhang; Druv Pai; Xudong Wang; Chandan Singh; Jianwei Yang; Jianfeng Gao 001; Yi Ma 001 (CoRR, 2025)

Attention-Only Transformers via Unrolled Subspace Denoising. - Peng Wang 098; Yifu Lu; Yaodong Yu; Druv Pai; Qing Qu 001; Yi Ma 001 (CoRR, 2025)