ProbAct: A Probabilistic Activation Function for Deep Neural Networks

26 May 2019

Papers citing "ProbAct: A Probabilistic Activation Function for Deep Neural Networks"

26 / 26 papers shown

Title
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference Kumar Shridhar F. Laumann Marcus Liwicki BDL UQCV 65 172 0 08 Jan 2019
The Quest for the Golden Activation Function Mina Basirat P. Roth 41 53 0 02 Aug 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 61 180 0 29 May 2018
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 88 419 0 02 Dec 2017
Searching for Activation Functions Prajit Ramachandran Barret Zoph Quoc V. Le 62 602 0 16 Oct 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh Tackgeun You Jonghwan Mun Bohyung Han NoLa 61 198 0 14 Oct 2017
Kafnets: kernel-based non-parametric activation functions for neural networks Simone Scardapane S. Van Vaerenbergh Simone Totaro A. Uncini 31 12 0 13 Jul 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 334 2,496 0 08 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 323 4,667 0 15 Mar 2017
Activation Ensembles for Deep Neural Networks Mark Harmon Diego Klabjan 137 35 0 24 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 615 5,748 0 05 Dec 2016
Natural-Parameter Networks: A Class of Probabilistic Neural Networks Hao Wang Xingjian Shi Dit-Yan Yeung BDL 62 83 0 02 Nov 2016
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks Ludovic Trottier Philippe Giguère B. Chaib-draa 65 199 0 30 May 2016
Noisy Activation Functions Çağlar Gülçehre Marcin Moczulski Misha Denil Yoshua Bengio 32 283 0 01 Mar 2016
Deep Learning with S-shaped Rectified Linear Activation Units Xiaojie Jin Chunyan Xu Jiashi Feng Yunchao Wei Junjun Xiong Shuicheng Yan 276 217 0 22 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 259 5,502 0 23 Nov 2015
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 62 544 0 21 Nov 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 154 1,878 0 20 May 2015
Empirical Evaluation of Rectified Activations in Convolutional Network Bing Xu Naiyan Wang Tianqi Chen Mu Li 127 2,901 0 05 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 96 940 0 18 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 246 18,534 0 06 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.2K 99,991 0 04 Sep 2014
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 204 16,311 0 30 Apr 2014
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 340 3,099 0 15 Aug 2013
Maxout Networks Ian Goodfellow David Warde-Farley M. Berk Mirza Aaron Courville Yoshua Bengio OOD 208 2,176 0 18 Feb 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 414 7,650 0 03 Jul 2012