Title
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 480 2 0 14 Mar 2025
Spatial-aware decision-making with ring attractors in reinforcement learning systems Marcos Negre Saura Richard Allmendinger Theodore Papamarkou Wei Pan 420 0 0 17 Feb 2025
Legitimate ground-truth-free metrics for deep uncertainty classification scoring Arthur Pignet Chiara Regniez John Klein 137 1 0 30 Oct 2024
Trajectory Flow Matching with Applications to Clinical Time Series Modeling Xi Zhang Yuan Pu Yuki Kawamura Andrew Loza Yoshua Bengio Dennis L. Shung Alexander Tong OOD AI4TS MedIm 89 7 0 28 Oct 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov Hampus Linander UQCV 96 19 0 19 Feb 2024
Class Uncertainty: A Measure to Mitigate Class Imbalance Z. S. Baltaci K. Oksuz S. Kuzucu K. Tezoren B. K. Konar A. Ozkan Emre Akbas Sinan Kalkan 128 2 0 23 Nov 2023
Plex: Towards Reliability using Pretrained Large Model Extensions Dustin Tran J. Liu Michael W. Dusenberry Du Phan Mark Collier ... D. Sculley Y. Gal Zoubin Ghahramani Jasper Snoek Balaji Lakshminarayanan VLM 108 126 0 15 Jul 2022
Excess risk analysis for epistemic uncertainty with application to variational inference Futoshi Futami Tomoharu Iwata N. Ueda Issei Sato Masashi Sugiyama UQCV 73 1 0 02 Jun 2022
Conformal Prediction with Temporal Quantile Adjustments Zhen Lin Shubhendu Trivedi Jimeng Sun AI4TS 105 19 0 20 May 2022
Adaptive Conformal Predictions for Time Series Margaux Zaffran Aymeric Dieuleveut Olivier Féron Y. Goude Julie Josse AI4TS 182 133 0 15 Feb 2022
Uncertainty estimation under model misspecification in neural network regression Maria R. Cervera Rafael Dätwyler Francesco DÁngelo Hamza Keurti Benjamin Grewe Christian Henning 52 6 0 23 Nov 2021
On out-of-distribution detection with Bayesian neural networks Francesco DÁngelo Christian Henning BDL UQCV 55 6 0 12 Oct 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification Anastasios Nikolas Angelopoulos Stephen Bates OOD 201 622 0 15 Jul 2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs Satyen Kale Ayush Sekhari Karthik Sridharan 210 29 0 11 Jul 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio Moksh Jain Maksym Korablyov Doina Precup Yoshua Bengio 101 331 0 08 Jun 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 83 96 0 07 Jun 2021
Deep Ensembles from a Bayesian Perspective L. Hoffmann Clemens Elster UD BDL UQCV 50 37 0 27 May 2021
A statistical framework for efficient out of distribution detection in deep neural networks Matan Haroush Tzviel Frostig R. Heller Daniel Soudry OODD 78 39 0 25 Feb 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip Torr Y. Gal UD UQCV PER BDL 94 154 0 23 Feb 2021
On Statistical Bias In Active Learning: How and When To Fix It Sebastian Farquhar Y. Gal Tom Rainforth TDI HAI 42 85 0 27 Jan 2021
Minimum Excess Risk in Bayesian Learning Aolin Xu Maxim Raginsky 410 40 0 29 Dec 2020
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung Willie Neiswanger I. Char J. Schneider UQCV 166 88 0 18 Nov 2020
Uncertainty Sets for Image Classifiers using Conformal Prediction Anastasios Nikolas Angelopoulos Stephen Bates Jitendra Malik Michael I. Jordan UQCV 205 337 0 29 Sep 2020
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 68 17 0 08 Jul 2020
Regression Prior Networks A. Malinin Sergey Chervontsev Ivan Provilkov Mark Gales BDL UQCV 53 38 0 20 Jun 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 171 451 0 17 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 79 84 0 16 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 70 184 0 16 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data Polina Kirichenko Pavel Izmailov A. Wilson OODD 93 275 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 76 102 0 15 Jun 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 50 20 0 16 May 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 57 215 0 14 May 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 63 55 0 04 Mar 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 165 493 0 17 Feb 2020
Aleatoric and Epistemic Uncertainty with Random Forests M. Shaker Eyke Hüllermeier BDL UD PER 57 72 0 03 Jan 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 244 1,415 0 21 Oct 2019
Deep Evidential Regression Alexander Amini Wilko Schwarting A. Soleimany Daniela Rus EDL PER BDL UD UQCV 81 440 0 07 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 86 465 0 03 Oct 2019
Epistemic Uncertainty Sampling Vu-Linh Nguyen Sebastien Destercke Eyke Hüllermeier PER UD 55 49 0 31 Aug 2019
Behaviour Suite for Reinforcement Learning Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 82 183 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 170 1,695 0 06 Jun 2019
Learning Loss for Active Learning Donggeun Yoo In So Kweon UQCV 85 660 0 09 May 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 69 236 0 30 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 172 3,435 0 28 Mar 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 74 277 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 84 808 0 07 Feb 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning David Janz Jiri Hron Przemysław Mazur Katja Hofmann José Miguel Hernández-Lobato Sebastian Tschiatschek 93 52 0 15 Oct 2018
A Tutorial on Bayesian Optimization P. Frazier GP 109 1,788 0 08 Jul 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 182 996 0 05 Jun 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 133 1,662 0 14 Mar 2018