Dropout Inference in Bayesian Neural Networks with Alpha-divergences

8 March 2017

Papers citing "Dropout Inference in Bayesian Neural Networks with Alpha-divergences"

49 / 49 papers shown

Title
Particle-based Online Bayesian Sampling Yifan Yang Chang-rui Liu Zhengze Zhang BDL 50 7 0 28 Feb 2023
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig Hampus Linander BDL UQCV 40 5 0 15 Dec 2022
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics Kamélia Daudel Joe Benton Yuyang Shi Arnaud Doucet DRL 26 9 0 12 Oct 2022
Predictive Inference with Feature Conformal Prediction Jiaye Teng Chuan Wen Dinghuai Zhang Yoshua Bengio Yang Gao Yang Yuan 38 26 0 01 Oct 2022
On the use of uncertainty in classifying Aedes Albopictus mosquitoes Gereziher W. Adhane Mohammad Mahdi Dehshibi David Masip 30 7 0 29 Oct 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 66 1,118 0 07 Jul 2021
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs Lorena Qendro Sangwon Ha R. D. Jong Partha P. Maji AAML FedML MQ 28 7 0 13 May 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng Xiao Yang Shizhen Xu Hang Su Jun Zhu BDL AAML 30 62 0 27 Mar 2021
The Hidden Uncertainty in a Neural Networks Activations Janis Postels Hermann Blum Yannick Strümpler Cesar Cadena Roland Siegwart Luc Van Gool Federico Tombari UQCV 44 22 0 05 Dec 2020
Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images J. E. Arco A. Ortiz J. Ramírez Francisco J. Martínez-Murcia Yudong Zhang Juan M Gorriz UQCV 43 3 0 27 Nov 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks Theodoros Tsiligkaridis UQCV 22 7 0 19 Oct 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 29 617 0 14 Jul 2020
Selective Dyna-style Planning Under Limited Model Capacity Zaheer Abbas Samuel Sokota Erin J. Talvitie Martha White 48 32 0 05 Jul 2020
SINVAD: Search-based Image Space Navigation for DNN Image Classifier Test Input Generation Sungmin Kang R. Feldt S. Yoo AAML 31 32 0 19 May 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 45 77 0 11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 24 34 0 05 Feb 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
Active Learning for Deep Detection Neural Networks H. H. Aghdam Abel Gonzalez-Garcia Joost van de Weijer Antonio M. López VLM ObjD 46 138 0 20 Nov 2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng Xiao Zhang F. Liang Guang Lin BDL 44 42 0 23 Oct 2019
Multi-person Pose Tracking using Sequential Monte Carlo with Probabilistic Neural Pose Predictor Masashi Okada Shinji Takenaka T. Taniguchi 48 4 0 16 Sep 2019
Variational Inference MPC for Bayesian Model-based Reinforcement Learning Masashi Okada T. Taniguchi 43 73 0 08 Jul 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 27 149 0 25 Apr 2019
Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks K. Posch J. Pilz UQCV BDL 29 28 0 02 Apr 2019
Variational Inference to Measure Model Uncertainty in Deep Neural Networks K. Posch J. Steinbrener J. Pilz UQCV BDL 22 28 0 26 Feb 2019
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien UQCV 35 24 0 08 Jan 2019
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic Mikael Henaff A. Canziani Yann LeCun OOD 47 122 0 08 Jan 2019
Building robust classifiers through generation of confident out of distribution examples K. Sricharan Ashok Srivastava OOD 18 31 0 01 Dec 2018
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting Artur Bekasov Iain Murray AAML BDL 26 14 0 29 Nov 2018
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 27 1,619 0 25 Nov 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 24 171 0 01 Oct 2018
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 34 402 0 21 Sep 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 62 44 0 12 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 31 68 0 06 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 95 960 0 05 Jun 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 36 6 0 19 May 2018
Hierarchical Novelty Detection for Visual Object Recognition Kibok Lee Kimin Lee Kyle Min Y. Zhang Jinwoo Shin Honglak Lee BDL 52 67 0 02 Apr 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 57 358 0 22 Mar 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 57 78 0 19 Feb 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks Mattias Teye Hossein Azizpour Kevin Smith BDL UQCV 33 240 0 18 Feb 2018
Uncertainty Estimates for Efficient Neural Network-based Dialogue Policy Optimisation Christopher Tegho Paweł Budzianowski Milica Gasic 43 8 0 30 Nov 2017
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 70 877 0 26 Nov 2017
Variational Inference based on Robust Divergences Futoshi Futami Issei Sato Masashi Sugiyama BDL OOD 10 66 0 18 Oct 2017
Deep and Confident Prediction for Time Series at Uber Lingxue Zhu N. Laptev BDL AI4TS 46 344 0 06 Sep 2017
From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning Jingkuan Song Yuyu Guo Lianli Gao Xuelong Li Alan Hanjalic Heng Tao Shen 40 219 0 08 Aug 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 41 18 0 02 Jun 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 57 587 0 22 May 2017
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 213 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 299 9,202 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 270 7,646 0 03 Jul 2012