Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

6 June 2015

Papers citing "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

50 / 1,180 papers shown

Title
Bayesian Generative Active Deep Learning Toan M. Tran Thanh-Toan Do Ian Reid G. Carneiro 6 134 0 26 Apr 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 11 149 0 25 Apr 2019
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation Subhashis Hazarika Haoyu Li Ko-Chih Wang Han-Wei Shen Ching-Shan Chou 21 20 0 19 Apr 2019
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout I. Cortés-Ciriano A. Bender OOD 18 47 0 12 Apr 2019
Effective and Efficient Dropout for Deep Convolutional Neural Networks Shaofeng Cai Jinyang Gao Gang Chen Beng Chin Ooi Wei Wang Meihui Zhang BDL 13 53 0 06 Apr 2019
Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks K. Posch J. Pilz UQCV BDL 9 28 0 02 Apr 2019
Variational Adversarial Active Learning Samarth Sinha Sayna Ebrahimi Trevor Darrell GAN DRL VLM SSL 23 570 0 31 Mar 2019
Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN Alireza Koochali P. Schichtel Sheraz Ahmed Andreas Dengel AI4TS 14 72 0 29 Mar 2019
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models T. Vishnu Diksha Garg Pankaj Malhotra L. Vig Gautam M. Shroff UQCV 17 15 0 23 Mar 2019
Interpreting Neural Networks Using Flip Points Roozbeh Yousefzadeh D. O’Leary AAML FAtt 16 17 0 21 Mar 2019
BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors Ali Harakeh Michael H. W. Smart Steven L. Waslander BDL UQCV 18 115 0 09 Mar 2019
Prostate Segmentation from 3D MRI Using a Two-Stage Model and Variable-Input Based Uncertainty Measure Huitong Pan Brandon Yushan Feng Quan Chen C. Meyer Xue Feng 12 16 0 06 Mar 2019
Robust Grasp Planning Over Uncertain Shape Completions Jens Lundell Francesco Verdoja Ville Kyrki 3DPC 17 57 0 02 Mar 2019
Architecting Dependable Learning-enabled Autonomous Systems: A Survey Chih-Hong Cheng Dhiraj Gulati Rongjie Yan 21 4 0 27 Feb 2019
Variational Inference to Measure Model Uncertainty in Deep Neural Networks K. Posch J. Steinbrener J. Pilz UQCV BDL 12 27 0 26 Feb 2019
Universal Dependency Parsing from Scratch Peng Qi Timothy Dozat Yuhao Zhang Christopher D. Manning 15 267 0 29 Jan 2019
Trust Region Value Optimization using Kalman Filtering Shirli Di-Castro Shashua Shie Mannor 6 7 0 23 Jan 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 28 854 0 18 Jan 2019
Input Prioritization for Testing Neural Networks Taejoon Byun Vaibhav Sharma Abhishek Vijayakumar Sanjai Rayadurgam D. Cofer AAML 21 67 0 11 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam S. Saria OOD 21 103 0 02 Jan 2019
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams Mohammad Kachuee Orpaz Goldstein Kimmo Karkkainen Sajad Darabi Majid Sarrafzadeh OOD 25 31 0 02 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 17 552 0 13 Dec 2018
Scene Recomposition by Learning-based ICP Hamid Izadinia S. M. Seitz 3DV 3DPC 17 14 0 13 Dec 2018
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data S. M. Kia A. Marquand 19 25 0 12 Dec 2018
Guided Dropout Rohit Keshari Richa Singh Mayank Vatsa BDL 13 37 0 10 Dec 2018
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 16 57 0 09 Dec 2018
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations Jacob Dumford Walter J. Scheirer AAML 11 116 0 07 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 16 1 0 05 Dec 2018
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 11 52 0 03 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 15 92 0 01 Dec 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 29 220 0 30 Nov 2018
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision M. Joneidi Alireza Zaeemzadeh Nazanin Rahnavard M. Shah 22 13 0 29 Nov 2018
Calibrating Uncertainties in Object Localization Task Buu Phan Rick Salay Krzysztof Czarnecki Vahdat Abdelzad Taylor Denouden Sachin Vernekar UQCV 20 22 0 27 Nov 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
Probabilistic Object Detection: Definition and Evaluation David Hall Feras Dayoub John Skinner Haoyang Zhang Dimity Miller Peter Corke G. Carneiro A. Angelova Niko Sünderhauf UQCV 29 111 0 27 Nov 2018
Sequential Neural Methods for Likelihood-free Inference Conor Durkan George Papamakarios Iain Murray BDL 28 24 0 21 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 22 392 0 19 Nov 2018
Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees Myriam Tami Marianne Clausel Emilie Devijver A. Dulac Éric Gaussier Stefan Janaqi M. Chèbre UQCV 16 0 0 27 Oct 2018
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation Radek Mackowiak Philip Lenz Omair Ghori Ferran Diego O. Lange Carsten Rother 31 108 0 23 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Metropolis-Hastings view on variational inference and adversarial training Kirill Neklyudov Evgenii Egorov Pavel Shvechikov Dmitry Vetrov GAN 15 13 0 16 Oct 2018
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models Yinan Li Xiao Liu Fang Liu 26 7 0 11 Oct 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
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 37 65 0 08 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 12 82 0 02 Oct 2018
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods Apratim Bhattacharyya Mario Fritz Bernt Schiele UQCV 19 46 0 01 Oct 2018
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI Jörg Sander B. D. de Vos J. Wolterink Ivana Išgum 9 59 0 27 Sep 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 11 397 0 21 Sep 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection Dimity Miller Feras Dayoub Michael Milford Niko Sünderhauf 12 105 0 17 Sep 2018
A Full End-to-End Semantic Role Labeler, Syntax-agnostic Over Syntax-aware? Jiaxun Cai Shexia He Z. Li Zhao Hai 29 77 0 11 Aug 2018