| Rethinking the benefits of steerable features in 3d equivariant graph neural networks SH Wang, YC Hsu, J Baker, AL Bertozzi, J Xin, B Wang The Twelfth International Conference on Learning Representations, 2024 | 4 | 2024 |
| Learning pod of complex dynamics using heavy-ball neural odes J Baker, E Cherkaev, A Narayan, B Wang arXiv preprint arXiv:2202.12373, 2022 | 4 | 2022 |
| Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs J Baker, H Xia, Y Wang, E Cherkaev, A Narayan, L Chen, J Xin, ... arXiv preprint arXiv:2204.08621, 2022 | 3 | 2022 |
| Implicit Graph Neural Networks: A Monotone Operator Viewpoint J Baker, Q Wang, CD Hauck, B Wang | 2 | 2023 |
| Invariant Features for Accurate Predictions of Quantum Chemical UV-vis Spectra of Organic Molecules J Baker, ML Pasini, C Hauck | 1 | 2023 |
| User Manual-HydraGNN: Distributed PyTorch Implementation of Multi-Headed Graph Convolutional Neural Networks M Lupo Pasini, JY Choi, P Zhang, J Baker Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), 2023 | 1 | 2023 |
| Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs J Baker, E Cherkaev, A Narayan, B Wang Journal of Scientific Computing 95 (2), 54, 2023 | 1 | 2023 |
| An Explicit Frame Construction for Normalizing 3D Point Clouds J Baker, SH Wang, T de Fernex, B Wang Forty-first International Conference on Machine Learning, 2024 | | 2024 |
| Stable, Efficient, and Flexible Monotone Operator Implicit Graph Neural Networks J Baker, Q Wang, B Wang | | 2022 |
| Stabilized E (n)-Equivariant Graph Neural Networks-assisted Generative Models J Baker, Y Huang, SH Wang, ML Pasini, AL Bertozzi, B Wang | | |
| Regularized Lippmann-Schwinger-Lanczos algorithm for inverse scattering problems V Druskin, J Baker, E Cherkaev, S Moskow, M Zaslavsky 2023 Joint Mathematics Meetings (JMM 2023), 0 | | |
