Multipole Graph Neural Operator for Parametric Partial Differential Equations. - Zongyi Li; Nikola B. Kovachki; Kamyar Azizzadenesheli; Burigede Liu; Andrew M. Stuart; Kaushik Bhattacharya; Anima Anandkumar (NeurIPS, 2020)

Neural Operator: Graph Kernel Network for Partial Differential Equations. - Zongyi Li; Nikola B. Kovachki; Kamyar Azizzadenesheli; Burigede Liu; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (CoRR, 2020)

Fourier Neural Operator for Parametric Partial Differential Equations. - Zongyi Li; Nikola Borislavov Kovachki; Kamyar Azizzadenesheli; Burigede Liu; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (ICLR, 2021)

Markov Neural Operators for Learning Chaotic Systems. - Zongyi Li; Nikola B. Kovachki; Kamyar Azizzadenesheli; Burigede Liu; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (CoRR, 2021)

Neural Operator: Learning Maps Between Function Spaces. - Nikola B. Kovachki; Zongyi Li; Burigede Liu; Kamyar Azizzadenesheli; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (CoRR, 2021)

Physics-Informed Neural Operator for Learning Partial Differential Equations. - Zongyi Li; Hongkai Zheng; Nikola B. Kovachki; David Jin; Haoxuan Chen; Burigede Liu; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2021)

Learning Chaotic Dynamics in Dissipative Systems. - Zongyi Li; Miguel Liu-Schiaffini; Nikola B. Kovachki; Kamyar Azizzadenesheli; Burigede Liu; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (NeurIPS, 2022)

A Learning-Based Optimal Uncertainty Quantification Method and Its Application to Ballistic Impact Problems. - Xingsheng Sun; Burigede Liu (CoRR, 2022)

Learning Dissipative Dynamics in Chaotic Systems (Datasets). - Zongyi Li; Miguel Liu-Schiaffini; Nikola Borislavov Kovachki; Burigede Liu; Kamyar Azizzadenesheli; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (Zenodo, 2022)

Towards Quantum Computational Mechanics. - Burigede Liu; Michael Ortiz; Fehmi Cirak (CoRR, 2023)

Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs. - Nikola B. Kovachki; Zongyi Li; Burigede Liu; Kamyar Azizzadenesheli; Kaushik Bhattacharya; Andrew M. Stuart; Anima Anandkumar (J. Mach. Learn. Res., 2023)

Fourier Neural Operator with Learned Deformations for PDEs on General Geometries. - Zongyi Li; Daniel Zhengyu Huang; Burigede Liu; Anima Anandkumar (J. Mach. Learn. Res., 2023)

Learning Markovian Homogenized Models in Viscoelasticity. - Kaushik Bhattacharya; Burigede Liu; Andrew M. Stuart; Margaret Trautner (Multiscale Model. Simul., 2023)

RVE-based virtual testing for investigation of the shear behaviour of cross-ply composites. - Siamak S. Shishvan; Azam Rahgouy; Burigede Liu (Eng. Comput., 2024)

A Learning-based Domain Decomposition Method. - Rui Wu; Nikola B. Kovachki; Burigede Liu (CoRR, 2025)