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• Characterizing possible failure modes in physics-informed neural networks
  2021 · 115 citations
• A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions
  2023 · 84 citations
• Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
  2024 · 4 citations
• A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs
  2021 · 4 citations
• AutoIP: A United Framework to Integrate Physics into Gaussian Processes
  2022 · 3 citations
• HyResPINNs: A Hybrid Residual Physics-Informed Neural Network Architecture Designed to Balance Expressiveness and Trainability
  2024 · 1 citations
• Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels
  2023 · 1 citations
• Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
  2023 · 1 citations
• StFT: Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction
  2025
• Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data
  2025
• Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
  2024
• ElastoGen: 4D Generative Elastodynamics
  2024