Title
Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing Fabian Denoodt José Oramas UQCV 176 0 0 19 Mar 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 128 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 465 0 0 03 Jan 2025
Likelihood approximations via Gaussian approximate inference Thang D. Bui 66 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 70 0 0 07 Aug 2024
A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou Benjamin Eysenbach Frank Nielsen Artur Dubrawski UQCV 107 2 0 16 Jun 2024
Uncertainty Quantification Metrics for Deep Regression Simon Kristoffersson Lind Ziliang Xiong Per-Erik Forssén Volker Kruger UQCV 72 6 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 72 0 0 18 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 149 34 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 113 2 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 Gabriel Loaiza-Ganem OODD 101 12 0 27 Mar 2024
A Survey of Machine Learning for Estimating Workload: Considering Unknown Tasks Josh Bhagat Smith Julie A. Adams 101 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 116 6 0 07 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 112 5 0 02 Feb 2024
Transferable Candidate Proposal with Bounded Uncertainty Kyeongryeol Go Kye-Hyeon Kim 71 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 56 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 41 4 0 02 Jul 2023
Beyond AUROC & co. for evaluating out-of-distribution detection performance Galadrielle Humblot-Renaux Sergio Escalera T. Moeslund OODD 78 5 0 26 Jun 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 111 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 70 3 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 193 24 0 26 Feb 2023
Variational Linearized Laplace Approximation for Bayesian Deep Learning Luis A. Ortega Simón Rodríguez Santana Daniel Hernández-Lobato BDL UQCV 135 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 75 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-Hsuan Yang Hartwig Adam Laurent Itti Balaji Lakshminarayanan Jiaping Zhao VLM 111 37 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 267 24 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 69 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 Torr P. Dokania Ser-Nam Lim OODD 52 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 143 76 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 144 126 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 113 5 0 22 Jun 2022
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 293 453 0 17 Jun 2020