On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

30 March 2022

Sanyam Kapoor

Papers citing "On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification"

34 / 34 papers shown

Title
Learning Hyperparameters via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 63 0 0 03 Feb 2025
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 40 0 0 28 Jan 2025
Temperature Optimization for Bayesian Deep Learning Kenyon Ng Chris van der Heide Liam Hodgkinson Susan Wei BDL 33 0 0 08 Oct 2024
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities Charlotte Bunne Yusuf Roohani Yanay Rosen Ankit Gupta Xikun Zhang ... Theofanis Karaletsos Aviv Regev Emma Lundberg J. Leskovec Stephen R. Quake 42 18 0 18 Sep 2024
Learning to Explore for Stochastic Gradient MCMC Seunghyun Kim Seohyeon Jung Seonghyeon Kim Juho Lee BDL 25 1 0 17 Aug 2024
Flat Posterior Does Matter For Bayesian Model Averaging Sungjun Lim Jeyoon Yeom Sooyon Kim Hoyoon Byun Jinho Kang Yohan Jung Jiyoung Jung Kyungwoo Song AAML BDL 40 0 0 21 Jun 2024
Cooperative learning of Pl@ntNet's Artificial Intelligence algorithm: how does it work and how can we improve it? Tanguy Lefort Antoine Affouard Benjamin Charlier J. Lombardo Mathias Chouet Hervé Goëau Joseph Salmon P. Bonnet Alexis Joly 37 0 0 05 Jun 2024
Robust Classification by Coupling Data Mollification with Label Smoothing Markus Heinonen Ba-Hien Tran Michael Kampffmeyer Maurizio Filippone 65 0 0 03 Jun 2024
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning Fahimeh Fakour Ali Mosleh Ramin Ramezani UQCV UD PER 38 1 0 01 Jun 2024
Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring Rules Paul Hofman Yusuf Sale Eyke Hüllermeier UQCV UD PER 38 5 0 18 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 54 23 0 17 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms Ziyu Wang Chris Holmes UQCV 27 2 0 28 Mar 2024
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation Yidong Zhao João Tourais Iain Pierce Christian Nitsche T. Treibel Sebastian Weingartner Artur M. Schweidtmann Qian Tao BDL UQCV 25 5 0 04 Mar 2024
Can a Confident Prior Replace a Cold Posterior? Martin Marek Brooks Paige Pavel Izmailov UQCV BDL 19 4 0 02 Mar 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 22 3 0 16 Feb 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 35 27 0 01 Feb 2024
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks Nikita Kotelevskii Samuel Horváth Karthik Nandakumar Martin Takáč Maxim Panov UQCV FedML OOD 17 7 0 18 Dec 2023
Understanding the Detrimental Class-level Effects of Data Augmentation Polina Kirichenko Mark Ibrahim Randall Balestriero Diane Bouchacourt Ramakrishna Vedantam Hamed Firooz Andrew Gordon Wilson 35 12 0 07 Dec 2023
Second-Order Uncertainty Quantification: A Distance-Based Approach Yusuf Sale Viktor Bengs Michele Caprio Eyke Hüllermeier PER UQCV UD 20 18 0 02 Dec 2023
On the Out-of-Distribution Coverage of Combining Split Conformal Prediction and Bayesian Deep Learning Paul Scemama Ariel Kapusta 20 0 0 21 Nov 2023
If there is no underfitting, there is no Cold Posterior Effect Yijie Zhang Yi-Shan Wu Luis A. Ortega A. Masegosa UQCV 13 1 0 02 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 54 18 0 28 Sep 2023
The fine print on tempered posteriors Konstantinos Pitas Julyan Arbel 20 1 0 11 Sep 2023
A Novel Bayes' Theorem for Upper Probabilities Michele Caprio Yusuf Sale Eyke Hüllermeier Insup Lee 13 10 0 13 Jul 2023
Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty? Yusuf Sale Michele Caprio Eyke Hüllermeier UD 8 25 0 16 Jun 2023
Training, Architecture, and Prior for Deterministic Uncertainty Methods Bertrand Charpentier Chenxiang Zhang Stephan Günnemann UQCV OOD AI4CE 26 6 0 10 Mar 2023
Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics Hanlin Yu M. Hartmann Bernardo Williams Arto Klami BDL 14 4 0 09 Mar 2023
Credal Bayesian Deep Learning Michele Caprio Souradeep Dutta Kuk Jin Jang Vivian Lin Radoslav Ivanov O. Sokolsky Insup Lee OOD BDL UQCV 21 18 0 19 Feb 2023
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization Jonas Geiping Micah Goldblum Gowthami Somepalli Ravid Shwartz-Ziv Tom Goldstein A. Wilson 21 35 0 12 Oct 2022
Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors Gianluca Detommaso Alberto Gasparin A. Wilson Cédric Archambeau UQCV BDL 29 3 0 17 Jul 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 45 56 0 23 Feb 2022
Theoretical characterization of uncertainty in high-dimensional linear classification Lucas Clarté Bruno Loureiro Florent Krzakala Lenka Zdeborová 16 20 0 07 Feb 2022
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 10 636 0 20 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016