Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity

12 September 2023

Papers citing "Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity"

17 / 17 papers shown

Title
Properties of the ENCE and other MAD-based calibration metrics P. Pernot 40 5 0 17 May 2023
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification Cameron J Gruich Varun Madhavan Yixin Wang B. Goldsmith 45 10 0 06 Feb 2023
Uncertainty quantification for predictions of atomistic neural networks Luis Itza Vazquez-Salazar Eric D. Boittier Markus Meuwly 21 15 0 14 Jul 2022
Reliable Neural Networks for Regression Uncertainty Estimation Tony Tohme Kevin Vanslette K. Youcef-Toumi UQCV BDL 49 15 0 16 Sep 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 71 72 0 06 Sep 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification Anastasios Nikolas Angelopoulos Stephen Bates OOD 172 615 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 205 1,146 0 07 Jul 2021
Improving Conditional Coverage via Orthogonal Quantile Regression Shai Feldman Stephen Bates Yaniv Romano 71 43 0 01 Jun 2021
Local Calibration: Metrics and Recalibration Rachel Luo Aadyot Bhatnagar Yu Bai Shengjia Zhao Huan Wang Caiming Xiong Silvio Savarese Stefano Ermon Edward Schmerling Marco Pavone 37 14 0 22 Feb 2021
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung Willie Neiswanger I. Char J. Schneider UQCV 138 88 0 18 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 258 1,911 0 12 Nov 2020
Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and a Path to Best Practices for Machine Learning in Chemistry G. Vishwakarma Aditya Sonpal J. Hachmann 79 48 0 30 Sep 2020
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction Lior Hirschfeld Kyle Swanson Kevin Kaichuang Yang Regina Barzilay Connor W. Coley 72 191 0 20 May 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 204 1,405 0 21 Oct 2019
Evaluating and Calibrating Uncertainty Prediction in Regression Tasks Dan Levi Liran Gispan Niv Giladi Ethan Fetaya UQCV 78 143 0 28 May 2019
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 154 9,390 0 09 Feb 2018
Conditional validity of inductive conformal predictors V. Vovk 203 416 0 12 Sep 2012