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• Tackling the Curse of Dimensionality with Physics-Informed Neural Networks
  2023 · 17 citations
• When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?
  2021 · 12 citations
• State-space models are accurate and efficient neural operators for dynamical systems
  2024 · 11 citations
• Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology
  2022 · 11 citations
• Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks
  2024 · 9 citations
• Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs
  2023 · 9 citations
• Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks
  2023 · 7 citations
• Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations
  2024 · 5 citations
• Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
  2024 · 2 citations
• D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
  2023 · 1 citations
• Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity
  2026