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Neural Networks

11,300 papers

Papers per year

Papers

Invariant Physics-Informed Neural Networks for Ordinary Differential Equations JMLR 2024
Improved Random Features for Dot Product Kernels JMLR 2024
Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization JMLR 2024
The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis JMLR 2024
Memory of recurrent networks: Do we compute it right? JMLR 2024
Random Fully Connected Neural Networks as Perturbatively Solvable Hierarchies JMLR 2024
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems JMLR 2024
Commutative Scaling of Width and Depth in Deep Neural Networks JMLR 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
Memorization With Neural Nets: Going Beyond the Worst Case JMLR 2024
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time JMLR 2024
A Rainbow in Deep Network Black Boxes JMLR 2024
Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning JMLR 2024
Operator learning without the adjoint JMLR 2024
KerasCV and KerasNLP: Multi-framework Models JMLR 2024
Scaled Conjugate Gradient Method for Nonconvex Optimization in Deep Neural Networks JMLR 2024
Deep Backward and Galerkin Methods for the Finite State Master Equation JMLR 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks JMLR 2024
Interpretable data-driven model predictive control of building energy systems using SHAP L4DC 2024
Physics-informed Neural Networks with Unknown Measurement Noise L4DC 2024
Piecewise regression via mixed-integer programming for MPC L4DC 2024
Parameter-adaptive approximate MPC: Tuning neural-network controllers without retraining L4DC 2024
Understanding the difficulty of solving Cauchy problems with PINNs L4DC 2024
Neural operators for boundary stabilization of stop-and-go traffic L4DC 2024
Learning flow functions of spiking systems L4DC 2024