Tractable Function-Space Variational Inference in Bayesian Neural Networks

28 December 2023

Papers citing "Tractable Function-Space Variational Inference in Bayesian Neural Networks"

31 / 31 papers shown

Title
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know Shireen Kudukkil Manchingal Fabio Cuzzolin 56 0 0 08 May 2025
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 113 0 0 04 May 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 155 0 0 14 Mar 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 92 12 0 28 Jan 2025
Functional Stochastic Gradient MCMC for Bayesian Neural Networks Mengjing Wu Junyu Xuan Jie Lu BDL 18 0 0 25 Sep 2024
Low-Budget Simulation-Based Inference with Bayesian Neural Networks Arnaud Delaunoy Maxence de la Brassinne Bonardeaux S. Mishra-Sharma Gilles Louppe 46 2 0 27 Aug 2024
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 40 4 0 10 Aug 2024
Sequential Gaussian Variational Inference for Nonlinear State Estimation applied to Robotic Applications Min-Won Seo Solmaz S. Kia 48 0 0 07 Jul 2024
Generative vs. Discriminative modeling under the lens of uncertainty quantification Elouan Argouarc'h François Desbouvries Eric Barat Eiji Kawasaki UQCV 46 0 0 13 Jun 2024
One-Shot Federated Learning with Bayesian Pseudocoresets Tim d'Hondt Mykola Pechenizkiy Robert Peharz FedML 37 0 0 04 Jun 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification Kaizheng Wang Fabio Cuzzolin Keivan K1 Shariatmadar David Moens Hans Hallez UQCV BDL 85 6 0 23 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 43 1 0 27 Apr 2024
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation Luhuan Wu Sinead Williamson UQCV 43 6 0 18 Mar 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 40 27 0 01 Feb 2024
Function-Space Regularization in Neural Networks: A Probabilistic Perspective Tim G. J. Rudner Sanyam Kapoor Shikai Qiu A. Wilson 37 12 0 28 Dec 2023
Should We Learn Most Likely Functions or Parameters? Shikai Qiu Tim G. J. Rudner Sanyam Kapoor Andrew Gordon Wilson 13 5 0 27 Nov 2023
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification L. J. L. Lopez Tim G. J. Rudner Karan Singhal 45 3 0 17 Nov 2023
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks Balhae Kim Hyungi Lee Juho Lee BDL 29 2 0 27 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 32 2 0 16 Oct 2023
EnSolver: Uncertainty-Aware Ensemble CAPTCHA Solvers with Theoretical Guarantees D. C. Hoang Behzad Ousat Amin Kharraz Cuong V Nguyen AAML 26 1 0 27 Jul 2023
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions Leo Klarner Tim G. J. Rudner M. Reutlinger Torsten Schindler Garrett M. Morris Charlotte M. Deane Yee Whye Teh OOD BDL 15 9 0 14 Jul 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift Florian Seligmann P. Becker Michael Volpp Gerhard Neumann UQCV 21 14 0 21 Jun 2023
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 31 5 0 19 Feb 2023
Random Grid Neural Processes for Parametric Partial Differential Equations Arnaud Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 28 11 0 26 Jan 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 39 124 0 15 Jul 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 14 4 0 24 Jun 2022
CARD: Classification and Regression Diffusion Models Xizewen Han Huangjie Zheng Mingyuan Zhou DiffM 49 109 0 15 Jun 2022
Split personalities in Bayesian Neural Networks: the case for full marginalisation David Yallup Will Handley Michael P. Hobson A. Lasenby Pablo Lemos 25 1 0 23 May 2022
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 273 0 28 Sep 2021
Scalable Uncertainty for Computer Vision with Functional Variational Inference Eduardo D C Carvalho R. Clark Andrea Nicastro Paul H. J. Kelly BDL UQCV 134 22 0 06 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015