A Simple Baseline for Bayesian Uncertainty in Deep Learning

7 February 2019

Dmitry Vetrov

Papers citing "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

37 / 187 papers shown

Title
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks Meet P. Vadera Adam D. Cobb B. Jalaeian Benjamin M. Marlin BDL UQCV 22 16 0 08 Jul 2020
A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images I. Laradji Pau Rodríguez López Frederic Branchaud-Charron Keegan Lensink Parmida Atighehchian William Parker David Vazquez Derek Nowrouzezahrai 33 19 0 07 Jul 2020
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions Ahmed Alaa M. Schaar UD UQCV BDL TDI 14 53 0 29 Jun 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 33 46 0 20 Jun 2020
Calibration of Model Uncertainty for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier BDL UQCV 29 18 0 20 Jun 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 28 94 0 18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 22 169 0 16 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 38 100 0 15 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 32 50 0 14 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 22 9 0 12 Jun 2020
Uncertainty Evaluation Metric for Brain Tumour Segmentation Raghav Mehta Angelos Filos Y. Gal Tal Arbel UQCV 24 16 0 28 May 2020
ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction Tian Guo N. Jamet Valentin Betrix Louis-Alexandre Piquet E. Hauptmann AIFin 11 30 0 05 May 2020
Calibrating Structured Output Predictors for Natural Language Processing Abhyuday N. Jagannatha Hong-ye Yu 20 28 0 09 Apr 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 19 220 0 16 Mar 2020
GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention Jiyang Xie Dongliang Chang Zhanyu Ma Guoqiang Zhang Jun Guo 26 25 0 10 Mar 2020
Iterative Averaging in the Quest for Best Test Error Diego Granziol Xingchen Wan Samuel Albanie Stephen J. Roberts 8 3 0 02 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences Daniel S. Brown Russell Coleman R. Srinivasan S. Niekum BDL 22 100 0 21 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 19 639 0 20 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
A Financial Service Chatbot based on Deep Bidirectional Transformers S. Yu Yuxin Chen Hussain Zaidi 14 33 0 17 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 33 314 0 15 Feb 2020
Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well Vipul Gupta S. Serrano D. DeCoste MoMe 30 55 0 07 Jan 2020
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 26 51 0 24 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 24 617 0 05 Dec 2019
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 20 368 0 28 Oct 2019
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 19 93 0 14 Oct 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 30 142 0 17 Jul 2019
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 34 31 0 28 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard E. Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 50 240 0 06 Jun 2019
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections R. Y. Rohekar Yaniv Gurwicz Shami Nisimov Gal Novik BDL UQCV 21 13 0 30 May 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark J. F. Gales UQCV 27 230 0 30 Apr 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 199 243 0 14 Jun 2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 0 05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 281 2,889 0 15 Sep 2016