AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks

18 September 2021

Papers citing "AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks"

9 / 59 papers shown

Title
All you need is a good init Dmytro Mishkin Jirí Matas ODL 82 610 0 19 Nov 2015
BinaryConnect: Training Deep Neural Networks with binary weights during propagations Matthieu Courbariaux Yoshua Bengio J. David MQ 198 2,984 0 02 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 432 43,234 0 11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 292 18,587 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.6K 149,842 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 236 4,665 0 21 Dec 2014
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 534 12,692 0 11 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 416 43,589 0 17 Sep 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 162 1,844 0 20 Dec 2013