Quality of Uncertainty Quantification for Bayesian Neural Network Inference

24 June 2019

Finale Doshi-Velez

Papers citing "Quality of Uncertainty Quantification for Bayesian Neural Network Inference"

29 / 29 papers shown

Title
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 64 0 0 03 Jan 2025
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise Yilong Hou Xi’an Li Jinran Wu You-Gan Wang 69 1 0 18 Aug 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 53 0 0 22 Jul 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 58 3 0 05 Jun 2024
Comparing the quality of neural network uncertainty estimates for classification problems Daniel Ries Joshua J. Michalenko T. Ganter R. Baiyasi Jason Adams UQCV BDL 29 1 0 11 Aug 2023
Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks Daniel Ries Jason Adams J. Zollweg BDL 16 1 0 11 Aug 2023
High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks Tim Rensmeyer Benjamin Craig D. Kramer Oliver Niggemann BDL 41 3 0 05 Apr 2023
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent Richard Archibald F. Bao Yanzhao Cao Hui‐Jie Sun 52 2 0 17 Dec 2022
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 34 7 0 01 Dec 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 32 36 0 25 Aug 2022
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization Hao Sun B. V. Breugel Jonathan Crabbé Nabeel Seedat M. Schaar 26 4 0 11 Jul 2022
SLOVA: Uncertainty Estimation Using Single Label One-Vs-All Classifier Bartosz Wójcik J. Grela Marek Śmieja Krzysztof Misztal Jacek Tabor UQCV 33 4 0 28 Jun 2022
CARD: Classification and Regression Diffusion Models Xizewen Han Huangjie Zheng Mingyuan Zhou DiffM 49 109 0 15 Jun 2022
Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection Bang Xiang Yong Alexandra Brintrup UQCV 28 24 0 25 Feb 2022
Coalitional Bayesian Autoencoders -- Towards explainable unsupervised deep learning Bang Xiang Yong Alexandra Brintrup 21 6 0 19 Oct 2021
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 38 8 0 10 Sep 2021
Bayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detection Bang Xiang Yong Tim Pearce Alexandra Brintrup OODD UQCV 19 6 0 28 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
Post-hoc loss-calibration for Bayesian neural networks Meet P. Vadera S. Ghosh Kenney Ng Benjamin M. Marlin UQCV BDL 43 7 0 13 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements L. Hoffmann I. Fortmeier Clemens Elster UQCV 25 28 0 01 Mar 2021
Avoiding Tampering Incentives in Deep RL via Decoupled Approval J. Uesato Ramana Kumar Victoria Krakovna Tom Everitt Richard Ngo Shane Legg 26 14 0 17 Nov 2020
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles Tárik S. Salem H. Langseth H. Ramampiaro UQCV 21 36 0 19 Jul 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 30 4 0 21 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 35 52 0 18 Nov 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 38 142 0 17 Jul 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015