Tri Dao - RankMe

98 papers A* 36A 2Journal 57Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI+HW 2035: Shaping the Next Decade. CoRR Deming Chen, Jason Cong, Azalia Mirhoseini, Christos Kozyrakis, Subhasish Mitra, Jinjun Xiong, Cliff Young, Anima Anandkumar, Michael L. Littman, Aron Kirschen, Sophia Shao, Serge Leef, Naresh R. Shanbhag, Dejan S. Milojicic, Michael Schulte, Gert Cauwenberghs, Jerry M. Chow, Tri Dao, Kailash Gopalakrishnan, Richard Ho, Hoshik Kim, Kunle Olukotun, David Z. Pan, Mark Ren, Dan Roth, Aarti Singh, Yizhou Sun, Yusu Wang, Yann LeCun, Ruchir Puri
2026	J	`jnl`	FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling. CoRR Ted Zadouri, Markus Hoehnerbach, Jay Shah, Timmy Liu, Vijay Thakkar, Tri Dao
2026	J	`jnl`	M CoRR Mayank Mishra, Shawn Tan, Ion Stoica, Joseph Gonzalez, Tri Dao
2026	J	`jnl`	Mamba-3: Improved Sequence Modeling using State Space Principles. CoRR Aakash Lahoti, Kevin Y. Li, Berlin Chen, Caitlin Wang, Aviv Bick, J. Zico Kolter, Tri Dao, Albert Gu
2026	J	`jnl`	Speculative Speculative Decoding. CoRR Tanishq Kumar, Tri Dao, Avner May
2026	J	`jnl`	When RL Meets Adaptive Speculative Training: A Unified Training-Serving System. CoRR Junxiong Wang, Fengxiang Bie, Jisen Li, Zhongzhu Zhou, Zelei Shao, Yubo Wang, Yinghui Liu, Qingyang Wu, Avner May, Sri Yanamandra, Yineng Zhang, Ce Zhang, Tri Dao, Percy Liang, Ben Athiwaratkun, Shuaiwen Leon Song, Chenfeng Xu, Xiaoxia Wu
2025	J	`jnl`	Beat the long tail: Distribution-Aware Speculative Decoding for RL Training. CoRR Zelei Shao, Vikranth Srivatsa, Sanjana Srivastava, Qingyang Wu, Alpay Ariyak, Xiaoxia Wu, Ameen Patel, Jue Wang, Percy Liang, Tri Dao, Ce Zhang, Yiying Zhang, Ben Athiwaratkun, Chenfeng Xu, Junxiong Wang
2025	J	`jnl`	Hardware-Efficient Attention for Fast Decoding. CoRR Ted Zadouri, Hubert Strauss, Tri Dao
2025	J	`jnl`	HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model. CoRR Mingqian Ma, Guoqing Liu, Chuan Cao, Pan Deng, Tri Dao, Albert Gu, Peiran Jin, Zhao Yang, Yingce Xia, Renqian Luo, Pipi Hu, Zun Wang, Yuan-Jyue Chen, Haiguang Liu, Tao Qin
2025	A*	`conf`	Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping. ICML Muru Zhang, Mayank Mishra, Zhongzhu Zhou, William Brandon, Jue Wang, Yoon Kim, Jonathan Ragan-Kelley, Shuaiwen Leon Song, Ben Athiwaratkun, Tri Dao
2025	J	`jnl`	Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping. CoRR Muru Zhang, Mayank Mishra, Zhongzhu Zhou, William Brandon, Jue Wang, Yoon Kim, Jonathan Ragan-Kelley, Shuaiwen Leon Song, Ben Athiwaratkun, Tri Dao
2025	J	`jnl`	Log-Linear Attention. CoRR Han Guo, Songlin Yang, Tarushii Goel, Eric P. Xing, Tri Dao, Yoon Kim
2025	J	`jnl`	Long-Context State-Space Video World Models. CoRR Ryan Po, Yotam Nitzan, Richard Zhang, Berlin Chen, Tri Dao, Eli Shechtman, Gordon Wetzstein, Xun Huang
2025	J	`jnl`	M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models. CoRR Junxiong Wang, Wen-Ding Li, Daniele Paliotta, Daniel Ritter, Alexander M. Rush, Tri Dao
2025	—	`conf`	Marconi: Prefix Caching for the Era of Hybrid LLMs. MLSys Rui Pan, Zhuang Wang, Zhen Jia, Can Karakus, Luca Zancato, Tri Dao, Yida Wang, Ravi Netravali
2025	J	`jnl`	Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining. CoRR Costin-Andrei Oncescu, Qingyang Wu, Wai Tong Chung, Robert Wu, Bryan Gopal, Junxiong Wang, Tri Dao, Ben Athiwaratkun
2025	J	`jnl`	SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations. CoRR Wentao Guo, Mayank Mishra, Xinle Cheng, Ion Stoica, Tri Dao
2025	J	`jnl`	Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners. CoRR Daniele Paliotta, Junxiong Wang, Matteo Pagliardini, Kevin Y. Li, Aviv Bick, J. Zico Kolter, Albert Gu, François Fleuret, Tri Dao
2024	J	`jnl`	An Empirical Study of Mamba-based Language Models. CoRR Roger Waleffe, Wonmin Byeon, Duncan Riach, Brandon Norick, Vijay Korthikanti, Tri Dao, Albert Gu, Ali Hatamizadeh, Sudhakar Singh, Deepak Narayanan, Garvit Kulshreshtha, Vartika Singh, Jared Casper, Jan Kautz, Mohammad Shoeybi, Bryan Catanzaro
2024	A*	`conf`	BitDelta: Your Fine-Tune May Only Be Worth One Bit. NeurIPS James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai
2024	J	`jnl`	BitDelta: Your Fine-Tune May Only Be Worth One Bit. CoRR James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai
2024	A*	`conf`	Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. ICML Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov
2024	J	`jnl`	Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. CoRR Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov
2024	A*	`conf`	FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning. ICLR Tri Dao
2024	A*	`conf`	FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision. NeurIPS Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao
2024	J	`jnl`	FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision. CoRR Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao
2024	A*	`conf`	Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers. NeurIPS Sukjun Hwang, Aakash Sunil Lahoti, Ratish Puduppully, Tri Dao, Albert Gu
2024	J	`jnl`	Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers. CoRR Sukjun Hwang, Aakash Lahoti, Tri Dao, Albert Gu
2024	J	`jnl`	Marconi: Prefix Caching for the Era of Hybrid LLMs. CoRR Rui Pan, Zhuang Wang, Zhen Jia, Can Karakus, Luca Zancato, Tri Dao, Ravi Netravali, Yida Wang
2024	A*	`conf`	Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads. ICML Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao
2024	J	`jnl`	Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads. CoRR Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao
2024	A*	`conf`	RedPajama: an Open Dataset for Training Large Language Models. NeurIPS Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	RedPajama: an Open Dataset for Training Large Language Models. CoRR Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	StarCoder 2 and The Stack v2: The Next Generation. CoRR Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian J. McAuley, Han Hu, Torsten Scholak, Sébastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, et al.
2024	A*	`conf`	The Mamba in the Llama: Distilling and Accelerating Hybrid Models. NeurIPS Junxiong Wang, Daniele Paliotta, Avner May, Alexander M. Rush, Tri Dao
2024	J	`jnl`	The Mamba in the Llama: Distilling and Accelerating Hybrid Models. CoRR Junxiong Wang, Daniele Paliotta, Avner May, Alexander M. Rush, Tri Dao
2024	A*	`conf`	Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality. ICML Tri Dao, Albert Gu
2024	J	`jnl`	Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality. CoRR Tri Dao, Albert Gu
2023	A*	`conf`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	J	`jnl`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	A*	`conf`	Effectively Modeling Time Series with Simple Discrete State Spaces. ICLR Michael Zhang, Khaled Kamal Saab, Michael Poli, Tri Dao, Karan Goel, Christopher Ré
2023	J	`jnl`	Effectively Modeling Time Series with Simple Discrete State Spaces. CoRR Michael Zhang, Khaled Kamal Saab, Michael Poli, Tri Dao, Karan Goel, Christopher Ré
2023	J	`jnl`	FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning. CoRR Tri Dao
2023	A*	`conf`	Hungry Hungry Hippos: Towards Language Modeling with State Space Models. ICLR Daniel Y. Fu, Tri Dao, Khaled Kamal Saab, Armin W. Thomas, Atri Rudra, Christopher Ré
2023	A*	`conf`	Hyena Hierarchy: Towards Larger Convolutional Language Models. ICML Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré
2023	J	`jnl`	Hyena Hierarchy: Towards Larger Convolutional Language Models. CoRR Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré
2023	J	`jnl`	Mamba: Linear-Time Sequence Modeling with Selective State Spaces. CoRR Albert Gu, Tri Dao
2023	A*	`conf`	Simple Hardware-Efficient Long Convolutions for Sequence Modeling. ICML Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Armin W. Thomas, Michael Zhang, Tri Dao, Atri Rudra, Christopher Ré
2023	J	`jnl`	Simple Hardware-Efficient Long Convolutions for Sequence Modeling. CoRR Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Armin W. Thomas, Michael Zhang, Tri Dao, Atri Rudra, Christopher Ré
2023	J	`jnl`	StarCoder: may the source be with you! CoRR Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy V, Jason Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Moustafa-Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries
2023	J	`jnl`	StarCoder: may the source be with you! Trans. Mach. Learn. Res. Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy V, Jason T. Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries
2022	A*	`conf`	ButterflyFlow: Building Invertible Layers with Butterfly Matrices. ICML Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon
2022	J	`jnl`	ButterflyFlow: Building Invertible Layers with Butterfly Matrices. CoRR Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon
2022	A*	`conf`	Decentralized Training of Foundation Models in Heterogeneous Environments. NeurIPS Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
2022	J	`jnl`	Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
2022	J	`jnl`	Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
2022	A*	`conf`	Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. NeurIPS Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
2022	A*	`conf`	FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. NeurIPS Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré
2022	J	`jnl`	FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. CoRR Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré
2022	J	`jnl`	Hungry Hungry Hippos: Towards Language Modeling with State Space Models. CoRR Tri Dao, Daniel Y. Fu, Khaled Kamal Saab, Armin W. Thomas, Atri Rudra, Christopher Ré
2022	A*	`conf`	Monarch: Expressive Structured Matrices for Efficient and Accurate Training. ICML Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré
2022	J	`jnl`	Monarch: Expressive Structured Matrices for Efficient and Accurate Training. CoRR Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré
2022	A*	`conf`	Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. ICLR Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré
2022	J	`jnl`	S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces. CoRR Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs, Preey Shah, Tri Dao, Stephen A. Baccus, Christopher Ré
2022	A*	`conf`	S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces. NeurIPS Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs, Preey Shah, Tri Dao, Stephen Baccus, Christopher Ré
2022	A*	`conf`	Transform Once: Efficient Operator Learning in Frequency Domain. NeurIPS Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon
2022	J	`jnl`	Transform Once: Efficient Operator Learning in Frequency Domain. CoRR Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon
2021	A*	`conf`	Catformer: Designing Stable Transformers via Sensitivity Analysis. ICML Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang
2021	A*	`conf`	Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers. NeurIPS Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré
2021	J	`jnl`	Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers. CoRR Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré
2021	A*	`conf`	Knowledge Distillation as Semiparametric Inference. ICLR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	J	`jnl`	Knowledge Distillation as Semiparametric Inference. CoRR Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey
2021	A*	`conf`	MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré
2021	J	`jnl`	Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. CoRR Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré
2021	A*	`conf`	Rethinking Neural Operations for Diverse Tasks. NeurIPS Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar
2021	J	`jnl`	Rethinking Neural Operations for Diverse Tasks. CoRR Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar
2021	J	`jnl`	Scatterbrain: Unifying Sparse and Low-rank Attention Approximation. CoRR Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré
2021	A*	`conf`	Scatterbrain: Unifying Sparse and Low-rank Attention. NeurIPS Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré
2020	A*	`conf`	HiPPO: Recurrent Memory with Optimal Polynomial Projections. NeurIPS Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré
2020	J	`jnl`	HiPPO: Recurrent Memory with Optimal Polynomial Projections. CoRR Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré
2020	A*	`conf`	Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. ICLR Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré
2020	J	`jnl`	Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. CoRR Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré
2019	A*	`conf`	A Kernel Theory of Modern Data Augmentation. ICML Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Ré
2019	A	`conf`	Adaptive Hashing for Model Counting. UAI Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon
2019	A*	`conf`	Approximating the Permanent by Sampling from Adaptive Partitions. NeurIPS Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon
2019	J	`jnl`	Approximating the Permanent by Sampling from Adaptive Partitions. CoRR Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon
2019	A*	`conf`	Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. ICML Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré
2019	J	`jnl`	Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. CoRR Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré
2019	A	`conf`	Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation. AISTATS Jian Zhang, Avner May, Tri Dao, Christopher Ré
2019	A*	`conf`	On the Downstream Performance of Compressed Word Embeddings. NeurIPS Avner May, Jian Zhang, Tri Dao, Christopher Ré
2019	J	`jnl`	On the Downstream Performance of Compressed Word Embeddings. CoRR Avner May, Jian Zhang, Tri Dao, Christopher Ré
2018	J	`jnl`	A Kernel Theory of Modern Data Augmentation. CoRR Tri Dao, Albert Gu, Alexander J. Ratner, Virginia Smith, Christopher De Sa, Christopher Ré
2018	A*	`conf`	Learning Compressed Transforms with Low Displacement Rank. NeurIPS Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré
2018	J	`jnl`	Learning Compressed Transforms with Low Displacement Rank. CoRR Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré
2018	—	`conf`	Learning Invariance with Compact Transforms. ICLR (Workshop) Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher Ré
2018	J	`jnl`	Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation. CoRR Jian Zhang, Avner May, Tri Dao, Christopher Ré
2017	—	`conf`	Gaussian Quadrature for Kernel Features. NIPS Tri Dao, Christopher De Sa, Christopher Ré
2017	J	`jnl`	Gaussian Quadrature for Kernel Features. CoRR Tri Dao, Christopher De Sa, Christopher Ré