Bayesian Inference for Large Scale Image Classification

9 August 2019

Papers citing "Bayesian Inference for Large Scale Image Classification"

20 / 20 papers shown

Title
Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation Yinsong Chen Samson S. Yu Zhong Li Chee Peng Lim BDL 78 0 0 01 Jul 2025
Piecewise Deterministic Markov Processes for Bayesian Neural Networks Ethan Goan Dimitri Perrin Kerrie Mengersen Clinton Fookes 67 0 0 17 Feb 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 101 21 0 15 Dec 2022
On the optimization and pruning for Bayesian deep learning X. Ke Yanan Fan BDL UQCV 75 1 0 24 Oct 2022
Low-Precision Stochastic Gradient Langevin Dynamics Ruqi Zhang A. Wilson Chris De Sa BDL 63 14 0 20 Jun 2022
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data Charlie Kirkwood T. Economou H. Odbert N. Pugeault 47 0 0 25 Jan 2022
Structured Stochastic Gradient MCMC Antonios Alexos Alex Boyd Stephan Mandt BDL 73 13 0 19 Jul 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4TS 92 71 0 25 May 2021
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise Jannik Schmitt Stefan Roth UQCV 45 6 0 15 Mar 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 82 109 0 24 Feb 2021
DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting Dongxian Wu Liyao (Mars) Gao X. Xiong Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu FedML 75 27 0 12 Feb 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 133 141 0 12 Feb 2021
All You Need is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran Simone Rossi Dimitrios Milios Maurizio Filippone OOD BDL 73 61 0 25 Nov 2020
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting Adam D. Cobb Brian Jalaian BDL 86 76 0 14 Oct 2020
Predictive Complexity Priors Eric T. Nalisnick Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV 106 19 0 18 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 86 215 0 14 May 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 95 61 0 19 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 105 320 0 15 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 72 27 0 25 Jan 2020
Distance-Based Learning from Errors for Confidence Calibration Chen Xing Sercan O. Arik Zizhao Zhang Tomas Pfister FedML 71 39 0 03 Dec 2019