neural network initialization

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training NeurIPS 2021 Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network ICLR 2021 Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract) AAAI 2021 The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization NeurIPS 2021 Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? ICML 2020 Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP ICLR 2020 Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function AISTATS 2019 Good Initializations of Variational Bayes for Deep Models ICML 2019 One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS 2019 How to Start Training: The Effect of Initialization and Architecture NeurIPS 2018 The emergence of spectral universality in deep networks AISTATS 2018 Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation NeurIPS 2018 The Shattered Gradients Problem: If resnets are the answer, then what is the question? ICML 2017 Improved Neural Network Initialization by Grouping Context-Dependent Targets for Acoustic Modeling Interspeech 2016