Particlewnn: A Weak-Form Deep Learning Framework for Solving Partial Differential Equations and Inverse Problems
Published in arxiv.org, 2023
Publications
You can also find my articles on my Google Scholar profile.
Preprints
Journal Articles
Design-GenNO: A Physics-Informed Generative Model with Neural Operators for Inverse Microstructure Design
Published in Computer Methods in Applied Mechanics and Engineering 450 (2026): 118597, 2025
DGenNO: a novel physics-aware neural operator for solving forward and inverse PDE problems based on deep, generative probabilistic modeling
Published in Journal of Computational Physics 538 (2025): 114137, 2025
Solving optimal control problems of rigid-body dynamics with collisions using the hybrid minimum principle
Published in Communications in Nonlinear Science and Numerical Simulation 143 (2025): 108603, 2025
PSP-GEN: Stochastic inversion of the Process–Structure–Property chain in materials design through deep, generative probabilistic modeling
Published in Acta Materialia 284 (2025): 120600, 2024
Weak neural variational inference for solving bayesian inverse problems without forward models: applications in elastography
Published in Computer Methods in Applied Mechanics and Engineering 433 (2025): 117493, 2024
Uncertainty-driven spiral trajectory for robotic peg-in-hole assembly
Published in IEEE Robotics and Automation Letters 7.3 (2022): 6661-6668, 2022
Numerical solution of inverse problems by weak adversarial networks
Published in Inverse Problems 36.11 (2020): 115003, 2020
Weak adversarial networks for high-dimensional partial differential equations
Published in Journal of Computational Physics 411 (2020): 109409, 2020
A jump stochastic differential equation approach for influence prediction on heterogenous networks
Published in Communications in Mathematical Sciences 18.8 (2020), 2020
Conference Papers
A machine learning enhanced algorithm for the optimal landing problem
Published in Mathematical and Scientific Machine Learning. PMLR, 2022, 2022