Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks

18 February 2015

José Miguel Hernández-Lobato

Papers citing "Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks"

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Title
Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums Jialin Yu Laila Alrajhi Anoushka Harit Zhongtian Sun Alexandra I. Cristea Lei Shi BDL UQCV 16 8 0 26 Apr 2021
On Batch Normalisation for Approximate Bayesian Inference Jishnu Mukhoti P. Dokania Philip H. S. Torr Y. Gal BDL UQCV 21 4 0 24 Dec 2020
Confidence Estimation via Auxiliary Models Charles Corbière Nicolas Thome A. Saporta Tuan-Hung Vu Matthieu Cord P. Pérez TPM 21 47 0 11 Dec 2020
The Hidden Uncertainty in a Neural Networks Activations Janis Postels Hermann Blum Yannick Strümpler César Cadena Roland Siegwart Luc Van Gool Federico Tombari UQCV 14 22 0 05 Dec 2020
Provably-Robust Runtime Monitoring of Neuron Activation Patterns Chih-Hong Cheng AAML 17 12 0 24 Nov 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks Theodoros Tsiligkaridis UQCV 12 7 0 19 Oct 2020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 34 27 0 19 Oct 2020
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles U. Sarawgi W. Zulfikar Rishab Khincha Pattie Maes PER UQCV BDL UD 11 7 0 25 Sep 2020
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 10 45 0 11 Sep 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 19 199 0 22 Jun 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 15 45 0 20 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 17 100 0 15 Jun 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán Umang Bhatt T. Adel Adrian Weller José Miguel Hernández-Lobato UQCV BDL 32 111 0 11 Jun 2020
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation Hong Joo Lee S. T. Kim Hakmin Lee Nassir Navab Yong Man Ro UQCV 6 7 0 21 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 13 60 0 17 May 2020
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 12 51 0 24 Dec 2019
Bayesian Graph Convolutional Neural Networks using Node Copying Soumyasundar Pal Florence Regol Mark J. Coates BDL GNN 14 12 0 08 Nov 2019
Thompson Sampling via Local Uncertainty Zhendong Wang Mingyuan Zhou 6 18 0 30 Oct 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 21 29 0 28 Sep 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 22 14 0 26 Aug 2019
Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation Janis Postels Francesco Ferroni Huseyin Coskun Nassir Navab Federico Tombari UQCV UD PER BDL 19 139 0 01 Aug 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 26 287 0 16 Jul 2019
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning Sebastian Farquhar Michael A. Osborne Y. Gal UQCV BDL 11 57 0 01 Jul 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 14 41 0 27 Jun 2019
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation Erik Englesson Hossein Azizpour UQCV 4 7 0 12 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 11 8 0 10 Jun 2019
Uncertainty-guided Continual Learning with Bayesian Neural Networks Sayna Ebrahimi Mohamed Elhoseiny Trevor Darrell Marcus Rohrbach CLL BDL 6 195 0 06 Jun 2019
Neural Likelihoods for Multi-Output Gaussian Processes M. Jankowiak J. Gardner UQCV BDL 17 3 0 31 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 11 14 0 27 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 21 8 0 23 May 2019
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions Tim Pearce Russell Tsuchida Mohamed H. Zaki Alexandra Brintrup A. Neely BDL 14 48 0 15 May 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam S. Saria OOD 11 103 0 02 Jan 2019
Building robust classifiers through generation of confident out of distribution examples K. Sricharan Ashok Srivastava OOD 6 31 0 01 Dec 2018
Bayesian graph convolutional neural networks for semi-supervised classification Yingxue Zhang Soumyasundar Pal Mark J. Coates Deniz Üstebay GNN BDL 19 227 0 27 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 14 392 0 19 Nov 2018
Deterministic Variational Inference for Robust Bayesian Neural Networks Anqi Wu Sebastian Nowozin Edward Meeds Richard E. Turner José Miguel Hernández-Lobato Alexander L. Gaunt UQCV AAML BDL 29 16 0 09 Oct 2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang Ruiyi Zhang Lawrence Carin Changyou Chen 8 46 0 05 Sep 2018
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 9 66 0 09 Aug 2018
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo Marton Havasi José Miguel Hernández-Lobato J. J. Murillo-Fuentes BDL 11 96 0 14 Jun 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 11 77 0 13 Jun 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 14 44 0 12 Jun 2018
Differentiable Compositional Kernel Learning for Gaussian Processes Shengyang Sun Guodong Zhang Chaoqi Wang Wenyuan Zeng Jiaman Li Roger C. Grosse BDL 11 69 0 12 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 15 68 0 06 Jun 2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen Ruiyi Zhang Wenlin Wang Bai Li Liqun Chen 11 86 0 29 May 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 17 180 0 29 May 2018
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization Yanshuai Cao G. Ding Kry Yik-Chau Lui Ruitong Huang GAN 8 19 0 09 May 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 22 366 0 26 Feb 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks Mattias Teye Hossein Azizpour Kevin Smith BDL UQCV 15 239 0 18 Feb 2018
Deep Neural Networks Learn Non-Smooth Functions Effectively Masaaki Imaizumi Kenji Fukumizu 13 123 0 13 Feb 2018
Bayesian Semisupervised Learning with Deep Generative Models Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV GAN 17 27 0 29 Jun 2017