Hannah Lawrence

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Partial Differential Equations

Query Complexity

Low Rank Approximation

Top Venues

Publications

Nadav Dym, Hannah Lawrence, Jonathan W. Siegel
Equivariant Frames and the Impossibility of Continuous Canonicalization. CoRR (2024)
Hannah Lawrence, Mitchell Tong Harris
Learning Polynomial Problems with SL(2, R)-Equivariance. ICLR (2024)
Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
On the hardness of learning under symmetries. ICLR (2024)
Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
On the hardness of learning under symmetries. CoRR (2024)
Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
Distilling Model Failures as Directions in Latent Space. ICLR (2023)
Hannah Lawrence, Mitchell Tong Harris
Learning Polynomial Problems with SL(2, ℝ) Equivariance. CoRR (2023)
Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. SODA (2023)
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR (2023)
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS (2023)
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR (2023)
Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. CoRR (2022)
Enric Boix Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
GULP: a prediction-based metric between representations. CoRR (2022)
Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
Distilling Model Failures as Directions in Latent Space. CoRR (2022)
Enric Boix-Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
GULP: a prediction-based metric between representations. NeurIPS (2022)
Hannah Lawrence, Bobak Toussi Kiani, Kristian G. Georgiev, Andrew K. Dienes
Implicit Bias of Linear Equivariant Networks. ICML (2022)
Hannah Lawrence, David Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. MSML (2021)
Hannah Lawrence, Kristian Georgiev, Andrew Dienes, Bobak Toussi Kiani
Implicit Bias of Linear Equivariant Networks. CoRR (2021)
Hannah Lawrence, David A. Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. CoRR (2020)
Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. NeurIPS (2020)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP (2020)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR (2019)
Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. CoRR (2019)