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Machine Learning and Computational Mathematics
89035 4381 pp. 1639-1670 -
Data-Driven, Physics-Based Feature Extraction from Fluid Flow Fields Using Convolutional Neural Networks
66841 6246 pp. 625-650 Open Access -
Dying ReLU and Initialization: Theory and Numerical Examples
86180 4199 pp. 1671-1706 -
Ensemble Gradient for Learning Turbulence Models from Indirect Observations
80767 3742 pp. 1269-1289 -
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Deep Unfitted Nitsche Method for Elliptic Interface Problems
52740 3338 pp. 1162-1179 -
Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions
53501 3565 pp. 1365-1384 -
Convergence Analysis for Over-Parameterized Deep Learning
28088 2178 pp. 71-103 -
Deep Network Approximation Characterized by Number of Neurons
69204 3704 pp. 1768-1811 -
Deep Potential: A General Representation of a Many-Body Potential Energy Surface
95388 6694 pp. 629-639 Open Access -
A Causality-DeepONet for Causal Responses of Linear Dynamical Systems
36425 1892 pp. 1194-1228 -
Convergence Analysis of PINNs with Over-Parameterization
9335 581 pp. 942-974