Daigavane, Ameya

10 publications

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems 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, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, 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 J. 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

ICLRW 2025 EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants Allan Dos Santos Costa, Ilan Mitnikov, Franco Pellegrini, Ameya Daigavane, Mario Geiger, Zhonglin Cao, Karsten Kreis, Tess Smidt, Emine Kucukbenli, Joseph Jacobson

NeurIPS 2025 JAMUN: Bridging Smoothed Molecular Dynamics and Score-Based Learning for Conformational Ensemble Generation Ameya Daigavane, Bodhi P. Vani, Darcy Davidson, Saeed Saremi, Joshua A Rackers, Joseph Kleinhenz

ICML 2025 The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Yuqing Xie, Ameya Daigavane, Mit Kotak, Tess Smidt

NeurIPSW 2024 JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling Ameya Daigavane, Bodhi P. Vani, Saeed Saremi, Joshua A Rackers, Joseph Kleinhenz

ICLR 2024 Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation Ameya Daigavane, Song Eun Kim, Mario Geiger, Tess Smidt

ICMLW 2024 The Price of Freedom: Exploring Tradeoffs Between Expressivity and Computational Efficiency in Equivariant Tensor Products YuQing Xie, Ameya Daigavane, Mit Kotak, Tess Smidt

NeurIPSW 2023 Privacy-Utility Trade-Offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure Tamara Müller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis

ICLRW 2022 Node-Level Differentially Private Graph Neural Networks Ameya Daigavane, Gagan Madan, Aditya Sinha, Abhradeep Guha Thakurta, Gaurav Aggarwal, Prateek Jain

Distill 2021 Understanding Convolutions on Graphs Ameya Daigavane, Balaraman Ravindran, Gaurav Aggarwal