Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users

14 July 2020

Laurent Valentin Jospin

Papers citing "Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users"

26 / 76 papers shown

Title
Deep Learning: A Bayesian Perspective Nicholas G. Polson Vadim Sokolov BDL 70 117 0 01 Jun 2017
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 32 594 0 13 Apr 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 250 4,667 0 15 Mar 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 127 198 0 08 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 35 1,717 0 08 Mar 2017
On Loss Functions for Deep Neural Networks in Classification Katarzyna Janocha Wojciech M. Czarnecki UQCV 50 549 0 18 Feb 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 52 193 0 13 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 451 5,748 0 05 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 241 4,612 0 10 Nov 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 88 3,420 0 07 Oct 2016
Towards Bayesian Deep Learning: A Framework and Some Existing Methods Hao Wang Dit-Yan Yeung BDL 34 225 0 24 Aug 2016
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 204 10,412 0 21 Jul 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 159 4,748 0 04 Jan 2016
Bayesian Dark Knowledge Masashi Sugiyama Vivek Rathod R. Garnett Max Welling BDL UQCV 43 258 0 14 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 135 1,500 0 08 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 247 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 425 9,233 0 06 Jun 2015
On Markov chain Monte Carlo methods for tall data Rémi Bardenet Arnaud Doucet Chris Holmes 56 276 0 11 May 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 153 19,448 0 09 Mar 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 57 940 0 18 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 577 149,474 0 22 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 128 14,831 1 21 Dec 2013
On Information Regularization Adrian Corduneanu Tommi Jaakkola 43 88 0 19 Oct 2012
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 163 2,605 0 29 Jun 2012
Multi-column Deep Neural Networks for Image Classification D. Ciresan U. Meier Jürgen Schmidhuber 74 3,935 0 13 Feb 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 123 4,275 0 18 Nov 2011