Ameya Daigavane

According to our database, Ameya Daigavane authored at least 11 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling.

Ameya Daigavane, Bodhi P. Vani, Saeed Saremi, Joseph Kleinhenz, Joshua Rackers

CoRR, 2024

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 E. Smidt, Emine Küçükbenli, Joseph Jacobson

CoRR, 2024

Differentially Private Graph Neural Networks for Medical Population Graphs and The Impact of The Graph Structure.

Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation.

Ameya Daigavane, Song Kim, Mario Geiger, Tess E. Smidt

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation.

Ameya Daigavane, Song Kim, Mario Geiger, Tess E. Smidt

CoRR, 2023

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, 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 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

CoRR, 2023

Privacy-Utility Trade-offs in Neural Networks for Medical Population Graphs: Insights from Differential Privacy and Graph Structure.

Tamara T. Mueller, Maulik Chevli, Ameya Daigavane, Daniel Rueckert, Georgios Kaissis

CoRR, 2023

2022

Resource Consumption and Radiation Tolerance Assessment for Data Analysis Algorithms Onboard Spacecraft.

Gary Doran, Ameya Daigavane, Kiri L. Wagstaff

IEEE Trans. Aerosp. Electron. Syst., 2022

Unsupervised detection of Saturn magnetic field boundary crossings from plasma spectrometer data.

Ameya Daigavane, Kiri L. Wagstaff, Gary Doran, Corey J. Cochrane, Caitriona M. Jackman, Abigail Rymer

Comput. Geosci., 2022

Learning Integrable Dynamics with Action-Angle Networks.

Ameya Daigavane, Arthur Kosmala, Miles D. Cranmer, Tess E. Smidt, Shirley Ho

CoRR, 2022

2021

Node-Level Differentially Private Graph Neural Networks.

Ameya Daigavane, Gagan Madan, Aditya Sinha, Abhradeep Guha Thakurta, Gaurav Aggarwal, Prateek Jain

CoRR, 2021