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Phase Diagram of Initial Condensation for Two-Layer Neural Networks
23713 1653 Pages:448-514 -
Understanding the Initial Condensation of Convolutional Neural Networks
8365 571 Pages:272-319 -
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections
41029 3473 Pages:532-550 -
Towards an Understanding of Residual Networks Using Neural Tangent Hierarchy (NTH)
293185 3086 Pages:692-760 -
BINet: Learn to Solve Partial Differential Equations with Boundary Integral Networks
35300 3230 Pages:275-305 -
Theory of the Frequency Principle for General Deep Neural Networks
44683 3662 Pages:484-507 -
Solving the Inverse Potential Problem in the Parabolic Equation by the Deep Neural Networks Method
13095 1238 Pages:852-883 -
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks
21368 1902 Pages:350-389 -
Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Condition
295185 3081 Pages:761-791 -
Enforcing Exact Boundary and Initial Conditions in the Deep Mixed Residual Method
40749 3415 Pages:748-775 -
Non-Lipschitz Attack: A More Sparse Adversarial Attack via Non-Lipschitz $ℓ_p$ Regularization
29125 2585 Pages:797-819 -
Unsupervised Deep Learning Meets Chan-Vese Model
295107 3119 Pages:662-691 -
Hartley Spectral Pooling for Deep Learning
41560 3758 Pages:518-529 -
Failure-Informed Adaptive Sampling for PINNs, Part III: Applications to Inverse Problems
23162 1700 Pages:636-670 -
Model Meets Deep Learning in Image Inverse Problems
44199 4100 Pages:365-386
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