Publications

Conference Proceedings

2024

[7d] E. Luk, E. Bach, R. Baptista, A.Stuart; Learning Optimal Filters Using Variational Inference; Machine Learning for Earth System Modeling (ML4ESM) Workshop at International Conference for Machine Learning (ICML) 2024, Vienna, Austria, July 26, 2024.
[Preprint]

[6d] S. C. Mouli, D. C. Maddix, S. Alizadeh, G. Gupta, A. Stuart, M. W. Mahoney, Y. Wang; Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs, Proceedings of the 41st International Conference on Machine Learning (ICML), PMLR, 2024.
[Preprint]

[5d] M. Karlbauer, D. M. Robinson, A. F. Ansari, B. Han, G. Gupta, Y. (Bernie) Wang, A. Stuart, M. Mahoney; Comparing and contrasting deep learning weather prediction backbones on Navier-Stokes dynamics; AI 4 Differential Equations in Science (ICLR 2024 Workshop).
[Preprint]

2021

[4d] Z. Li, M. Liu-Schiaffini, N. Kovachki, K. Azizzadenesheli, B. Liu, K. Bhattacharya, A. Stuart, A. Anandkumar; Learning Dissipative Dynamics in Chaotic Systems, Advances in Neural Information Processing Systems, Neurips 2022.
[Preprint]

[3d] Z. Li, N. Kovachki, K. Azizzadenesheli, B. Liu, K. Bhattacharya, A. Stuart, A. Anandkumar; Fourier Neural Operator for Parametric Partial Differential Equations. 9th International Conference on Learning Representations ICLR 2021.
[Preprint]

2020

[2d]  Z. Li, N. Kovachki, K. Azizzadenesheli, B. Liu, K. Bhattacharya, A. Stuart, A. Anandkumar; Multipole Graph Neural Operator for Parametric Partial Differential Equations, Advances in Neural Information Processing Systems, Neurips 2020, pages  6755--6766.
[Preprint]

[1d] Z. Li, N. Kovachki, K. Azizzadenesheli, B. Liu, K. Bhattacharya, A. Stuart, A. Anandkumar; Neural Operator: Graph Kernel Network for Partial Differential Equations.
[Preprint]