Beyond Marginal Uncertainty: How Accurately can Bayesian Regression
Models Estimate Posterior Predictive Correlations?

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Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?

6 November 2020

Roger C. Grosse

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Papers citing "Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?"

18 / 18 papers shown

Title
Active Fine-Tuning of Multi-Task Policies Marco Bagatella Jonas Hübotter Georg Martius Andreas Krause 149 0 0 07 Oct 2024
Making Better Use of Unlabelled Data in Bayesian Active Learning Freddie Bickford-Smith Adam Foster Tom Rainforth 110 4 0 26 Apr 2024
Active Few-Shot Fine-Tuning Jonas Hübotter Bhavya Sukhija Lenart Treven Yarden As Andreas Krause 98 1 0 13 Feb 2024
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 211 1 0 10 Oct 2023
Anchor Points: Benchmarking Models with Much Fewer Examples Rajan Vivek Kawin Ethayarajh Diyi Yang Douwe Kiela ALM 116 28 0 14 Sep 2023
BatchGFN: Generative Flow Networks for Batch Active Learning Shreshth A. Malik Salem Lahlou Andrew Jesson Moksh Jain Nikolay Malkin T. Deleu Yoshua Bengio Y. Gal AI4CE 68 2 0 26 Jun 2023
Prediction-Oriented Bayesian Active Learning Freddie Bickford-Smith Andreas Kirsch Sebastian Farquhar Y. Gal Adam Foster Tom Rainforth 87 36 0 17 Apr 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design Desi R. Ivanova Joel Jennings Tom Rainforth Cheng Zhang Adam Foster 100 3 0 27 Feb 2023
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities Andreas Kirsch Y. Gal FedML 95 23 0 01 Aug 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping Vikranth Dwaracherla Zheng Wen Ian Osband Xiuyuan Lu S. Asghari Benjamin Van Roy UQCV 96 20 0 08 Jun 2022
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling Andreas Kirsch Jannik Kossen Y. Gal UQCV BDL 97 3 0 18 May 2022
Evaluating High-Order Predictive Distributions in Deep Learning Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Xiuyuan Lu Benjamin Van Roy 81 10 0 28 Feb 2022
Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shift Tong Xia Jing Han Cecilia Mascolo OOD 82 11 0 16 Dec 2021
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 94 22 0 09 Oct 2021
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 60 8 0 10 Sep 2021
From Predictions to Decisions: The Importance of Joint Predictive Distributions Zheng Wen Ian Osband Chao Qin Xiuyuan Lu M. Ibrahimi Vikranth Dwaracherla Mohammad Asghari Benjamin Van Roy UQCV 91 22 0 20 Jul 2021
Epistemic Neural Networks Ian Osband Zheng Wen M. Asghari Vikranth Dwaracherla M. Ibrahimi Xiyuan Lu Benjamin Van Roy UQCV BDL 134 109 0 19 Jul 2021
Test Distribution-Aware Active Learning: A Principled Approach Against Distribution Shift and Outliers Andreas Kirsch Tom Rainforth Y. Gal OOD TTA 74 22 0 22 Jun 2021