Title
Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing Fabian Denoodt José Oramas UQCV 73 0 0 19 Mar 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 65 0 0 03 Feb 2025
Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images Xiaoge Zhang Tao Wang Chao Yan Fedaa Najdawi Kai Zhou Yuan Ma Yiu-ming Cheung Bradley Malin MedIm 42 0 0 03 Jan 2025
Likelihood approximations via Gaussian approximate inference Thang D. Bui 27 0 0 28 Oct 2024
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling Jian Xu Zhiqi Lin Shigui Li Min Chen Junmei Yang Delu Zeng John Paisley BDL 28 0 0 07 Aug 2024
A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou Benjamin Eysenbach Frank Nielsen Artur Dubrawski UQCV 46 2 0 16 Jun 2024
Uncertainty Quantification Metrics for Deep Regression Simon Kristoffersson Lind Ziliang Xiong Per-Erik Forssén Volker Kruger UQCV 22 3 0 07 May 2024
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning Jie Chen Pengfei Ou Yuxin Chang Hengrui Zhang Xiao-Yan Li E. H. Sargent Wei Chen 32 0 0 18 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 63 23 0 17 Apr 2024
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification Denis Huseljic Paul Hahn M. Herde Lukas Rauch Bernhard Sick 30 1 0 13 Apr 2024
A Geometric Explanation of the Likelihood OOD Detection Paradox Hamidreza Kamkari Brendan Leigh Ross Jesse C. Cresswell Anthony L. Caterini Rahul G. Krishnan G. Loaiza-Ganem OODD 26 9 0 27 Mar 2024
Workload Estimation for Unknown Tasks: A Survey of Machine Learning Under Distribution Shift Josh Bhagat Smith Julie A. Adams 21 0 0 20 Mar 2024
Open-Vocabulary Calibration for Fine-tuned CLIP Shuoyuan Wang Jindong Wang Guoqing Wang Bob Zhang Kaiyang Zhou Hongxin Wei VLM 33 5 0 07 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 36 5 0 02 Feb 2024
Transferable Candidate Proposal with Bounded Uncertainty Kyeongryeol Go Kye-Hyeon Kim 29 0 0 07 Dec 2023
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems Harry Li Steven Jorgensen J. Holodnak Allan B. Wollaber OOD UQCV 22 1 0 08 Aug 2023
Morse Neural Networks for Uncertainty Quantification Benoit Dherin Huiyi Hu Jie Jessie Ren Michael W. Dusenberry Balaji Lakshminarayanan UQCV AI4CE 21 4 0 02 Jul 2023
Beyond AUROC & co. for evaluating out-of-distribution detection performance Galadrielle Humblot-Renaux Sergio Escalera T. Moeslund OODD 19 4 0 26 Jun 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 61 1 0 26 May 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis OOD UQCV 19 2 0 08 Apr 2023
A Survey on Uncertainty Quantification Methods for Deep Learning Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Yukun Li BDL UQCV AI4CE 19 18 0 26 Feb 2023
Variational Linearized Laplace Approximation for Bayesian Deep Learning Luis A. Ortega Simón Rodríguez Santana Daniel Hernández-Lobato BDL UQCV 47 4 0 24 Feb 2023
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play J. Liu Krishnamurthy Dvijotham Jihyeon Janel Lee Quan Yuan Martin Strobel Balaji Lakshminarayanan Deepak Ramachandran 23 5 0 11 Feb 2023
Improving Zero-shot Generalization and Robustness of Multi-modal Models Yunhao Ge Jie Jessie Ren Andrew Gallagher Yuxiao Wang Ming Yang Hartwig Adam Laurent Itti Balaji Lakshminarayanan Jiaping Zhao VLM 29 34 0 04 Dec 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity Dennis Ulmer J. Frellsen Christian Hardmeier 187 22 0 20 Oct 2022
Efficient Bayesian Updates for Deep Learning via Laplace Approximations Denis Huseljic M. Herde Lukas Rauch Paul Hahn Zhixin Huang D. Kottke S. Vogt Bernhard Sick BDL 16 0 0 12 Oct 2022
Raising the Bar on the Evaluation of Out-of-Distribution Detection Jishnu Mukhoti Tsung-Yu Lin Bor-Chun Chen Ashish Shah Philip H. S. Torr P. Dokania Ser-Nam Lim OODD 15 4 0 24 Sep 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 57 71 0 19 Jul 2022
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 39 124 0 15 Jul 2022
Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection Ishaan Bhat J. Pluim M. Viergever Hugo J. Kuijf MedIm 21 4 0 22 Jun 2022
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 267 3,371 0 09 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 76 31 0 02 Mar 2020
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 73 31 0 13 Apr 2018
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 68 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015
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 296 39,198 0 01 Sep 2014
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 86 271 0 24 Feb 2014