Loss-Calibrated Approximate Inference in Bayesian Neural Networks

Loss-Calibrated Approximate Inference in Bayesian Neural Networks

10 May 2018

Stephen J. Roberts

Papers citing "Loss-Calibrated Approximate Inference in Bayesian Neural Networks"

16 / 16 papers shown

Title
Making Reliable and Flexible Decisions in Long-tailed Classification Bolian Li Ruqi Zhang 233 0 0 23 Jan 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 56 2 0 03 Jan 2025
Amortized Bayesian Decision Making for simulation-based models Mila Gorecki Jakob H. Macke Michael Deistler 27 1 0 05 Dec 2023
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers H. Coppock G. Nicholson Ivan Kiskin Vasiliki Koutra Kieran Baker ... Björn W. Schuller D. Pigoli S. Gilmour Stephen J. Roberts Chris Holmes 62 24 0 15 Dec 2022
On Calibrated Model Uncertainty in Deep Learning Biraja Ghoshal A. Tucker UQCV MedIm 27 10 0 15 Jun 2022
Loss-calibrated expectation propagation for approximate Bayesian decision-making Michael J. Morais Jonathan W. Pillow 49 6 0 10 Jan 2022
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
Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Development Bhargab Ghoshal Biraja Ghoshal S. Swift A. Tucker 22 3 0 20 Mar 2021
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 Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection Biraja Ghoshal A. Tucker UQCV OOD 24 378 0 22 Mar 2020
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo Adam D. Cobb A. G. Baydin Andrew Markham Stephen J. Roberts 8 32 0 14 Oct 2019
Correcting Predictions for Approximate Bayesian Inference Tomasz Kuśmierczyk J. Sakaya Arto Klami 21 10 0 11 Sep 2019
Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning Mike Walmsley Lewis Smith Chris J. Lintott Y. Gal S. Bamford ... K. Masters C. Scarlata B. Simmons R. Smethurst D. Wright 35 86 0 17 May 2019
Embedded deep learning in ophthalmology: Making ophthalmic imaging smarter Petteri Teikari Raymond P. Najjar L. Schmetterer D. Milea MedIm 27 27 0 13 Oct 2018
Taming the Cross Entropy Loss Manuel Martínez Rainer Stiefelhagen NoLa 26 46 0 11 Oct 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015