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On the Convergence and generalization of Physics Informed Neural Networks., , and . CoRR, (2020)Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations., , and . SIAM J. Sci. Comput., 42 (1): A292-A317 (2020)Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging., , and . CoRR, (2020)Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions., , , and . Neurocomputing, (2022)AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images., , , , , , , and . CoRR, (2021)Parallel Physics-Informed Neural Networks via Domain Decomposition., , and . CoRR, (2021)Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs., , , , and . CoRR, (2023)DeepOnet Based Preconditioning Strategies For Solving Parametric Linear Systems of Equations., and . CoRR, (2024)Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems., , , and . CoRR, (2021)Mechanical Characterization and Inverse Design of Stochastic Architected Metamaterials Using Neural Operators., , , , , and . CoRR, (2023)