Group Equivariant Fourier Neural Operators for Partial Differential Equations. - Jacob Helwig; Xuan Zhang; Cong Fu 003; Jerry Kurtin; Stephan Wojtowytsch; Shuiwang Ji (ICML, 2023)

Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction. - Cong Fu 003; Jacob Helwig; Shuiwang Ji (LoG, 2023)

SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. - Xuan Zhang; Jacob Helwig; Yuchao Lin; Yaochen Xie; Cong Fu 003; Stephan Wojtowytsch; Shuiwang Ji (ICLR, 2024)

Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. - Yuchao Lin; Jacob Helwig; Shurui Gui; Shuiwang Ji (ICML, 2024)

A Geometry-Aware Message Passing Neural Network for Modeling Aerodynamics over Airfoils. - Jacob Helwig; Xuan Zhang; Haiyang Yu 005; Shuiwang Ji (CoRR, 2024)

Algorithm 1045: A Covariate-Dependent Approach to Gaussian Graphical Modeling in R. - Jacob Helwig; Sutanoy Dasgupta; Peng Zhao 021; Bani K. Mallick; Debdeep Pati (ACM Trans. Math. Softw., 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)

A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling. - Jacob Helwig; Sai Sreeharsha Adavi; Xuan Zhang; Yuchao Lin; Felix S. Chim; Luke Takeshi Vizzini; Haiyang Yu 005; Muhammad Hasnain; Saykat Kumar Biswas; John J. Holloway; Narendra Singh; N. K. Anand; et al. (CoRR, 2025)

NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jocelyn Ahmed Mazari; Jean-Patrick Brunet; Abbas Kabalan; Fabien Casenave; Yuxin Ma; Giovanni Catalani; Jean Fesquet; Jacob Helwig; Xuan Zhang; et al. (CoRR, 2025)