WaiChing Sun
Orcid: 0000-0002-3078-5086Affiliations:
- Columbia University, Department of Civil Engineering and Engineering Mechanics, New York, NY, USA
According to our database1,
WaiChing Sun
authored at least 25 papers
between 2018 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables.
CoRR, 2024
2023
CoRR, 2023
Physics-constrained symbolic model discovery for polyconvex incompressible hyperelastic materials.
CoRR, 2023
Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria.
CoRR, 2023
Discovering interpretable elastoplasticity models via the neural polynomial method enabled symbolic regressions.
CoRR, 2023
CoRR, 2023
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties.
CoRR, 2023
2022
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter.
CoRR, 2022
Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity.
CoRR, 2022
2021
A new finite element level set reinitialization method based on the shifted boundary method.
J. Comput. Phys., 2021
MD-inferred neural network monoclinic finite-strain hyperelasticity models for β-HMX: Sobolev training and validation against physical constraints.
CoRR, 2021
Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings.
CoRR, 2021
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation.
CoRR, 2021
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph.
CoRR, 2021
2020
An accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data.
CoRR, 2020
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening.
CoRR, 2020
An immersed phase field fracture model for fluid-infiltrating porous media with evolving Beavers-Joseph-Saffman condition.
CoRR, 2020
A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks.
CoRR, 2020
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity.
CoRR, 2020
ILS-MPM: an implicit level-set-based material point method for frictional particulate contact mechanics of deformable particles.
CoRR, 2020
2019
A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation.
CoRR, 2019
2018
Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning.
CoRR, 2018