network initialization

Tuning the Frequencies: Robust Training for Sinusoidal Neural Networks CVPR 2025 VI^3NR: Variance Informed Initialization for Implicit Neural Representations CVPR 2025 Zero-cost Proxy for Adversarial Robustness Evaluation ICLR 2025 From Activation to Initialization: Scaling Insights for Optimizing Neural Fields CVPR 2024 Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory ICLR 2024 PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks JMLR 2024 Abide by the law and follow the flow: conservation laws for gradient flows NeurIPS 2023 A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel ICML 2023 Deep Random Projector: Accelerated Deep Image Prior CVPR 2023 Maximal Initial Learning Rates in Deep ReLU Networks ICML 2023 Neural tangent kernel at initialization: linear width suffices UAI 2023 Polarity Is All You Need to Learn and Transfer Faster ICML 2023 Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth ICLR 2023 Demystifying the Neural Tangent Kernel From a Practical Perspective: Can It Be Trusted for Neural Architecture Search Without Training? CVPR 2022 Fast Finite Width Neural Tangent Kernel ICML 2022 Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks NeurIPS 2022 On Scrambling Phenomena for Randomly Initialized Recurrent Networks NeurIPS 2022 Optimized Potential Initialization for Low-Latency Spiking Neural Networks AAAI 2022 Recent Advances on Neural Network Pruning at Initialization IJCAI 2022 Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) NeurIPS 2022 The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization NeurIPS 2022 A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network COLT 2021 How Does Topology Influence Gradient Propagation and Model Performance of Deep Networks With DenseNet-Type Skip Connections? CVPR 2021 PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data ICML 2021 Pruning Neural Networks at Initialization: Why Are We Missing the Mark? ICLR 2021