Subspace Inference for Bayesian Deep Learning

17 July 2019

Dmitry Vetrov

Papers citing "Subspace Inference for Bayesian Deep Learning"

30 / 30 papers shown

Title
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen Xinming Zhang Ninghui Li 102 1 0 28 Jan 2025
Reparameterization invariance in approximate Bayesian inference Hrittik Roy M. Miani Carl Henrik Ek Philipp Hennig Marvin Pfortner Lukas Tatzel Søren Hauberg BDL 47 8 0 05 Jun 2024
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design A. N. M. N. Abeer Sanket R. Jantre Nathan M. Urban Byung-Jun Yoon 49 1 0 30 Apr 2024
Implicit Variational Inference for High-Dimensional Posteriors Anshuk Uppal Kristoffer Stensbo-Smidt Wouter Boomsma J. Frellsen BDL 26 1 0 10 Oct 2023
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks Sanket R. Jantre Nathan M. Urban Xiaoning Qian Byung-Jun Yoon BDL UQCV 26 4 0 06 Sep 2023
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning Moonseok Choi Hyungi Lee G. Nam Juho Lee 32 2 0 24 May 2023
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 32 7 0 01 Dec 2022
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems Gilad Kutiel Regev Cohen Michael Elad Daniel Freedman UQCV 21 5 0 28 Nov 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 23 52 0 11 Nov 2022
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity Martin Gubri Maxime Cordy Mike Papadakis Yves Le Traon Koushik Sen AAML 35 51 0 26 Jul 2022
The Unreasonable Effectiveness of Deep Evidential Regression N. Meinert J. Gawlikowski Alexander Lavin UQCV EDL 177 35 0 20 May 2022
Low-Loss Subspace Compression for Clean Gains against Multi-Agent Backdoor Attacks Siddhartha Datta N. Shadbolt AAML 26 6 0 07 Mar 2022
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy Cole Hawkins Alec Koppel Zheng-Wei Zhang 42 4 0 18 Jan 2022
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 38 21 0 10 Oct 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 24 18 0 16 Sep 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 38 1,111 0 07 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 58 289 0 28 Jun 2021
Multivariate Deep Evidential Regression N. Meinert Alexander Lavin BDL PER EDL UQCV 35 21 0 13 Apr 2021
Learning Neural Network Subspaces Mitchell Wortsman Maxwell Horton Carlos Guestrin Ali Farhadi Mohammad Rastegari UQCV 27 85 0 20 Feb 2021
Bayesian Methods for Semi-supervised Text Annotation Kristian Miok Gregor Pirš Marko Robnik-Šikonja BDL 34 5 0 28 Oct 2020
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles U. Sarawgi W. Zulfikar Rishab Khincha Pattie Maes PER UQCV BDL UD 21 7 0 25 Sep 2020
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles Tárik S. Salem H. Langseth H. Ramampiaro UQCV 13 36 0 19 Jul 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks Meet P. Vadera Adam D. Cobb B. Jalaeian Benjamin M. Marlin BDL UQCV 27 16 0 08 Jul 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 38 46 0 20 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 41 100 0 15 Jun 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 639 0 20 Feb 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 32 93 0 14 Oct 2019
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
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,266 0 09 Jun 2012