Prediction-Oriented Bayesian Active Learning

17 April 2023

Freddie Bickford-Smith

Papers citing "Prediction-Oriented Bayesian Active Learning"

21 / 21 papers shown

Title
Distributionally Robust Active Learning for Gaussian Process Regression Shion Takeno Yoshito Okura Yu Inatsu Aoyama Tatsuya Tomonari Tanaka ... Noriaki Hashimoto Taro Murayama Hanju Lee Shinya Kojima Ichiro Takeuchi OOD GP 43 0 0 24 Feb 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 44 2 0 03 Jan 2025
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 91 1 0 27 Nov 2024
Active Fine-Tuning of Generalist Policies Marco Bagatella Jonas Hübotter Georg Martius Andreas Krause 32 0 0 07 Oct 2024
Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information Fedor Sergeev Paola Malsot Gunnar Rätsch Vincent Fortuin AI4TS 49 0 0 18 Jul 2024
CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training David Brandfonbrener Hanlin Zhang Andreas Kirsch Jonathan Richard Schwarz Sham Kakade 26 7 0 15 Jun 2024
Deep Bayesian Active Learning for Preference Modeling in Large Language Models L. Melo P. Tigas Alessandro Abate Yarin Gal 37 8 0 14 Jun 2024
On Subjective Uncertainty Quantification and Calibration in Natural Language Generation Ziyu Wang Chris Holmes UQLM 45 4 0 07 Jun 2024
Making Better Use of Unlabelled Data in Bayesian Active Learning Freddie Bickford-Smith Adam Foster Tom Rainforth 20 3 0 26 Apr 2024
Bayesian Active Learning for Censored Regression F. B. Hüttel Christoffer Riis Filipe Rodrigues Francisco Câmara Pereira 19 1 0 19 Feb 2024
Active Few-Shot Fine-Tuning Jonas Hübotter Bhavya Sukhija Lenart Treven Yarden As Andreas Krause 28 1 0 13 Feb 2024
Nesting Particle Filters for Experimental Design in Dynamical Systems Sahel Iqbal Adrien Corenflos Simo Särkkä Hany Abdulsamad 18 2 0 12 Feb 2024
DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design Clare Lyle Arash Mehrjou Pascal Notin Andrew Jesson Stefan Bauer Y. Gal Patrick Schwab 41 10 0 07 Dec 2023
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification Jacopo Talpini Fabio Sartori Marco Savi 22 2 0 05 Sep 2023
Deep Stochastic Processes via Functional Markov Transition Operators Jin Xu Emilien Dupont Kaspar Martens Tom Rainforth Yee Whye Teh 20 4 0 24 May 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 16 73 0 28 Feb 2023
Black-Box Batch Active Learning for Regression Andreas Kirsch 17 7 0 17 Feb 2023
Looking at the posterior: accuracy and uncertainty of neural-network predictions H. Linander Oleksandr Balabanov Henry Yang Bernhard Mehlig UQCV UD BDL 14 2 0 26 Nov 2022
Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning Andreas Kirsch Sebastian Farquhar Parmida Atighehchian Andrew Jesson Frederic Branchaud-Charron Y. Gal 23 20 0 22 Jun 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015