relu network

Critically Assessing the State of the Art in Neural Network Verification JMLR 2024 Deep Network Approximation: Beyond ReLU to Diverse Activation Functions JMLR 2024 Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization JMLR 2024 Depth Separation in Norm-Bounded Infinite-Width Neural Networks COLT 2024 Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization ICLR 2024 Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability AISTATS 2024 Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials COLT 2024 Expressivity of ReLU-Networks under Convex Relaxations ICLR 2024 Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks UAI 2024 Minimum width for universal approximation using ReLU networks on compact domain ICLR 2024 Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks NeurIPS 2024 Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024 Noisy Interpolation Learning with Shallow Univariate ReLU Networks ICLR 2024 Optimal Bump Functions for Shallow ReLU networks: Weight Decay, Depth Separation, Curse of Dimensionality JMLR 2024 Overcoming the Optimizer’s Curse: Obtaining Realistic Prescriptions from Neural Networks ICML 2024 Piecewise Linear Transformation – Propagating Aleatoric Uncertainty in Neural Networks AAAI 2024 Provable Accelerated Convergence of Nesterov’s Momentum for Deep ReLU Neural Networks ALT 2024 REGLO: Provable Neural Network Repair for Global Robustness Properties AAAI 2024 Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes NeurIPS 2024 The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks ICML 2024 Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks NeurIPS 2024 Topological Expressivity of ReLU Neural Networks COLT 2024 Topological obstruction to the training of shallow ReLU neural networks NeurIPS 2024 Abide by the law and follow the flow: conservation laws for gradient flows NeurIPS 2023 Achieve the Minimum Width of Neural Networks for Universal Approximation ICLR 2023