Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning

15 February 2020

Dmitry Vetrov

Papers citing "Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning"

48 / 48 papers shown

Title
Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis Chen Zhao Xuan Wang Tong Zhang Saqib Javed Mathieu Salzmann 3DGS 351 0 0 13 Mar 2025
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph Roman Vashurin Ekaterina Fadeeva Artem Vazhentsev Akim Tsvigun Daniil Vasilev ... Timothy Baldwin Timothy Baldwin Maxim Panov Artem Shelmanov Artem Shelmanov HILM 76 20 0 21 Jun 2024
CONFINE: Conformal Prediction for Interpretable Neural Networks Linhui Huang S. Lala N. Jha 79 2 0 01 Jun 2024
Enabling Uncertainty Estimation in Iterative Neural Networks Nikita Durasov Doruk Öner Jonathan Donier Hieu M. Le Pascal Fua UQCV 59 8 0 25 Mar 2024
Fine-tuning with Very Large Dropout Jianyu Zhang Léon Bottou 53 1 0 01 Mar 2024
Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks Youngkyoung Bae Seungwoong Ha Hawoong Jeong 73 2 0 02 Feb 2024
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 72 1 0 02 Nov 2023
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 38 95 0 18 Jun 2020
Hydra: Preserving Ensemble Diversity for Model Distillation Linh-Tam Tran Bastiaan S. Veeling Kevin Roth J. Swiatkowski Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Sebastian Nowozin Rodolphe Jenatton 36 58 0 14 Jan 2020
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 42 349 0 23 Sep 2019
Bayesian Inference for Large Scale Image Classification Jonathan Heek Nal Kalchbrenner UQCV BDL 70 33 0 09 Aug 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 98 1,667 0 06 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 41 298 0 04 Jun 2019
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex Yufei Cui Wuguannan Yao Qiao Li Antoni B. Chan Chun Jason Xue 16 4 0 29 May 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 43 482 0 02 Apr 2019
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off Yukun Ding Jinglan Liu Jinjun Xiong Yiyu Shi 28 13 0 05 Mar 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 33 196 0 19 Feb 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 37 275 0 11 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 52 801 0 07 Feb 2019
Inhibited Softmax for Uncertainty Estimation in Neural Networks Marcin Mo.zejko Mateusz Susik Rafal Karczewski UQCV 23 29 0 03 Oct 2018
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion Jacob Buckman Danijar Hafner George Tucker E. Brevdo Honglak Lee 38 329 0 04 Jul 2018
Adversarial Distillation of Bayesian Neural Network Posteriors Kuan-Chieh Wang Paul Vicol James Lucas Li Gu Roger C. Grosse R. Zemel UQCV GAN AAML BDL 29 56 0 27 Jun 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 70 1,257 0 30 May 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 70 1,632 0 14 Mar 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 119 903 0 28 Feb 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs T. Garipov Pavel Izmailov Dmitrii Podoprikhin Dmitry Vetrov A. Wilson UQCV 36 746 0 27 Feb 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks Mattias Teye Hossein Azizpour Kevin Smith BDL UQCV 67 240 0 18 Feb 2018
Uncertainty Estimation via Stochastic Batch Normalization Andrei Atanov Arsenii Ashukha Dmitry Molchanov Kirill Neklyudov Dmitry Vetrov UQCV BDL 42 47 0 13 Feb 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 199 9,663 0 25 Oct 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 88 5,746 0 14 Jun 2017
Snapshot Ensembles: Train 1, get M for free Gao Huang Yixuan Li Geoff Pleiss Zhuang Liu John E. Hopcroft Kilian Q. Weinberger OOD FedML UQCV 79 938 0 01 Apr 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 110 456 0 06 Mar 2017
Soft Weight-Sharing for Neural Network Compression Karen Ullrich Edward Meeds Max Welling 48 415 0 13 Feb 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 26 825 0 19 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 359 5,742 0 05 Dec 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 152 7,944 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 671 192,387 0 10 Dec 2015
Bayesian Dark Knowledge Masashi Sugiyama Vivek Rathod R. Garnett Max Welling BDL UQCV 39 258 0 14 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 80 1,500 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 336 9,221 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 47 1,876 0 20 May 2015
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger C. Grosse ODL 52 994 0 19 Mar 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 59 19,448 0 09 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 142 43,110 0 11 Feb 2015
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 144 43,481 0 17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 365 99,915 0 04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 542 39,328 0 01 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 43 14,831 1 21 Dec 2013