Node-Level Differentially Private Graph Neural Networks. - Ameya Daigavane; Gagan Madan; Aditya Sinha; Abhradeep Guha Thakurta; Gaurav Aggarwal; Prateek Jain 002 (CoRR, 2021)

Learning Integrable Dynamics with Action-Angle Networks. - Ameya Daigavane; Arthur Kosmala; Miles D. Cranmer; Tess E. Smidt; Shirley Ho (CoRR, 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)

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)

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)

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation. - Ameya Daigavane; Song Kim; Mario Geiger; Tess E. Smidt (CoRR, 2023)

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation. - Ameya Daigavane; Song Kim; Mario Geiger; Tess E. Smidt (ICLR, 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 (ISBI, 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)

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

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products. - Yuqing Xie 006; Ameya Daigavane; Mit Kotak; Tess E. Smidt (CoRR, 2025)