neural network width

A Depth Hierarchy for Computing the Maximum in ReLU Networks via Extremal Graph Theory COLT 2026 Defining Neural Network Architecture through Polytope Structures of Datasets ICML 2024 Even Sparser Graph Transformers NeurIPS 2024 Minimum width for universal approximation using ReLU networks on compact domain ICLR 2024 More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory ICLR 2024 Achieve the Minimum Width of Neural Networks for Universal Approximation ICLR 2023 Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation ICML 2023 Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis ICML 2022 Wide Neural Networks Forget Less Catastrophically ICML 2022 Non-asymptotic approximations of neural networks by Gaussian processes COLT 2021 Slimmable Generative Adversarial Networks AAAI 2021 Subquadratic Overparameterization for Shallow Neural Networks NeurIPS 2021 The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective NeurIPS 2021 On the Global Convergence of Training Deep Linear ResNets ICLR 2020