Variance Networks: When Expectation Does Not Meet Your Expectations

10 March 2018

Dmitry Vetrov

Papers citing "Variance Networks: When Expectation Does Not Meet Your Expectations"

20 / 20 papers shown

Title
Perceive With Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception Anushri Dixit Zhiting Mei Meghan Booker Mariko Storey-Matsutani Mariko Storey-Matsutani Allen Z. Ren Ola Shorinwa Anirudha Majumdar 140 6 0 13 Mar 2024
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 162 907 0 28 Feb 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs T. Garipov Pavel Izmailov Dmitrii Podoprikhin Dmitry Vetrov A. Wilson UQCV 54 746 0 27 Feb 2018
Variational Gaussian Dropout is not Bayesian Jiri Hron A. G. Matthews Zoubin Ghahramani 42 47 0 08 Nov 2017
Noisy Networks for Exploration Meire Fortunato M. G. Azar Bilal Piot Jacob Menick Ian Osband ... Rémi Munos Demis Hassabis Olivier Pietquin Charles Blundell Shane Legg 57 890 0 30 Jun 2017
Parameter Space Noise for Exploration Matthias Plappert Rein Houthooft Prafulla Dhariwal Szymon Sidor Richard Y. Chen Xi Chen Tamim Asfour Pieter Abbeel Marcin Andrychowicz 45 594 0 06 Jun 2017
Structured Bayesian Pruning via Log-Normal Multiplicative Noise Kirill Neklyudov Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 81 188 0 20 May 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 83 825 0 19 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 463 5,748 0 05 Dec 2016
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 102 2,331 0 12 Aug 2016
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 212 6,628 0 08 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 144 1,500 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 439 9,233 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 102 1,878 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 60 940 0 18 Feb 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 276 43,154 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 678 149,474 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 155 18,922 0 20 Dec 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 66 902 0 17 Feb 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 344 16,972 0 20 Dec 2013