Variational Bayesian Last Layers

17 April 2024

Papers citing "Variational Bayesian Last Layers"

30 / 30 papers shown

Title
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi Yibin Wang Ligong Han Huatian Zhang Hao Wang UQCV 183 2 0 07 Dec 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 113 1 0 31 May 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 123 25 0 07 Feb 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Philipp Reiser Javier Enrique Aguilar A. Guthke Paul-Christian Bürkner 100 2 0 08 Dec 2023
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 45 55 0 11 Nov 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 183 50 0 01 May 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 61 51 0 30 Mar 2022
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 201 312 0 28 Jun 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection Jie Jessie Ren Stanislav Fort J. Liu Abhijit Guha Roy Shreyas Padhy Balaji Lakshminarayanan UQCV 166 224 0 16 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 102 130 0 14 May 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 67 384 0 29 Apr 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 99 139 0 12 Feb 2021
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition Xueting Zhang Debin Meng Henry Gouk Timothy M. Hospedales BDL UQCV 83 72 0 08 Jan 2021
Learnable Uncertainty under Laplace Approximations Agustinus Kristiadi Matthias Hein Philipp Hennig UQCV BDL 54 30 0 06 Oct 2020
A statistical theory of cold posteriors in deep neural networks Laurence Aitchison UQCV BDL 44 70 0 13 Aug 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 57 4 0 21 Jun 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 53 213 0 14 May 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 77 286 0 24 Feb 2020
Continuous Meta-Learning without Tasks James Harrison Apoorva Sharma Chelsea Finn Marco Pavone CLL OOD 74 79 0 18 Dec 2019
Benchmarking the Neural Linear Model for Regression Sebastian W. Ober C. Rasmussen BDL 67 42 0 18 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 78 542 0 06 Dec 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 178 721 0 07 Jun 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 159 1,691 0 06 Jun 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 69 106 0 03 Apr 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 82 806 0 07 Feb 2019
Wide Residual Networks Sergey Zagoruyko N. Komodakis 326 7,980 0 23 May 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 236 885 0 06 Nov 2015
Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It Peter Grünwald T. V. Ommen 83 267 0 11 Dec 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 101 1,230 0 26 Sep 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 248 2,621 0 29 Jun 2012