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Epistemic Neural Networks

19 July 2021

Papers citing "Epistemic Neural Networks"

37 / 37 papers shown

Title
Uncertainty modeling for fine-tuned implicit functions A. Susmelj Mael Macuglia Nataša Tagasovska Reto Sutter Sebastiano Caprara Jean-Philippe Thiran E. Konukoglu 138 2 0 17 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 140 2 0 31 May 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 268 22 0 28 Feb 2024
Selective Uncertainty Propagation in Offline RL Sanath Kumar Krishnamurthy Shrey Modi Tanmay Gangwani S. Katariya Branislav Kveton A. Rangi OffRL 191 0 0 01 Feb 2023
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping Vikranth Dwaracherla Zheng Wen Ian Osband Xiuyuan Lu S. Asghari Benjamin Van Roy UQCV 84 20 0 08 Jun 2022
Evaluating High-Order Predictive Distributions in Deep Learning Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Xiuyuan Lu Benjamin Van Roy 57 10 0 28 Feb 2022
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 71 22 0 09 Oct 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Zachary Nado Neil Band Mark Collier Josip Djolonga Michael W. Dusenberry ... D. Sculley Balaji Lakshminarayanan Jasper Snoek Y. Gal Dustin Tran UQCV ELM 91 96 0 07 Jun 2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent NoLa 217 54 0 19 May 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 72 387 0 29 Apr 2021
Reinforcement Learning, Bit by Bit Xiuyuan Lu Benjamin Van Roy Vikranth Dwaracherla M. Ibrahimi Ian Osband Zheng Wen 57 70 0 06 Mar 2021
On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty Joost R. van Amersfoort Lewis Smith Andrew Jesson Oscar Key Y. Gal UQCV 71 104 0 22 Feb 2021
Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models Xiaofang Wang Dan Kondratyuk Eric Christiansen Kris Kitani Y. Alon Elad Eban 57 49 0 03 Dec 2020
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 90 213 0 13 Oct 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 56 121 0 11 Jul 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 211 451 0 17 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 77 185 0 16 Jun 2020
Acme: A Research Framework for Distributed Reinforcement Learning Matthew W. Hoffman Bobak Shahriari John Aslanides Gabriel Barth-Maron Nikola Momchev ... Srivatsan Srinivasan A. Cowie Ziyun Wang Bilal Piot Nando de Freitas 120 226 0 01 Jun 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 611 4,905 0 23 Jan 2020
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 123 629 0 05 Dec 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 183 1,702 0 06 Jun 2019
Do CIFAR-10 Classifiers Generalize to CIFAR-10? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD FedML ELM 171 414 0 01 Jun 2018
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 155 561 0 30 Apr 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 193 923 0 28 Feb 2018
Variational Gaussian Dropout is not Bayesian Jiri Hron A. G. Matthews Zoubin Ghahramani 55 47 0 08 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 135 1,099 0 01 Nov 2017
Ensemble Sampling Xiuyuan Lu Benjamin Van Roy 129 121 0 20 May 2017
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 59 599 0 13 Apr 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 100 307 0 22 Mar 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,719 0 15 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 73 1,739 0 08 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 348 4,635 0 10 Nov 2016
Bootstrapped Thompson Sampling and Deep Exploration Ian Osband Benjamin Van Roy 162 105 0 01 Jul 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 852 9,346 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015
Generalization and Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Zheng Wen 91 314 0 04 Feb 2014