Distribution Calibration for Regression

15 May 2019

Papers citing "Distribution Calibration for Regression"

29 / 29 papers shown

Title
Three Types of Calibration with Properties and their Semantic and Formal Relationships Rabanus Derr Jessie Finocchiaro Robert C. Williamson 38 0 0 25 Apr 2025
Calibrating Expressions of Certainty Peiqi Wang Barbara D. Lam Yingcheng Liu Ameneh Asgari-Targhi Rameswar Panda W. Wells Tina Kapur Polina Golland 32 1 0 06 Oct 2024
Calibrated Probabilistic Forecasts for Arbitrary Sequences Charles Marx Volodymyr Kuleshov Stefano Ermon AI4TS 36 1 0 27 Sep 2024
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks Dingyi Zhuang Yuheng Bu Guang Wang Shenhao Wang Jinhua Zhao BDL 32 1 0 13 Sep 2024
Orthogonal Causal Calibration Justin Whitehouse Christopher Jung Vasilis Syrgkanis Bryan Wilder Zhiwei Steven Wu CML 114 1 0 04 Jun 2024
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 58 1 0 02 Nov 2023
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics Charles Marx Sofian Zalouk Stefano Ermon 27 6 0 31 Oct 2023
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration Kemal Oksuz Thomas Joy P. Dokania UQCV 17 16 0 03 Jul 2023
Sharp Calibrated Gaussian Processes A. Capone Geoff Pleiss Sandra Hirche UQCV 29 4 0 23 Feb 2023
On the role of Model Uncertainties in Bayesian Optimization Jonathan Foldager Mikkel Jordahn Lars Kai Hansen Michael Riis Andersen 19 4 0 14 Jan 2023
Calibration tests beyond classification David Widmann Fredrik Lindsten Dave Zachariah 30 17 0 21 Oct 2022
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions Paweł Antoni Pierzchlewicz R. J. Cotton Mohammad Ali Bashiri Fabian H. Sinz 3DH 21 8 0 20 Oct 2022
Quantile-constrained Wasserstein projections for robust interpretability of numerical and machine learning models Marouane Il Idrissi Nicolas Bousquet Fabrice Gamboa Bertrand Iooss Jean-Michel Loubes 35 2 0 23 Sep 2022
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection Fabian Küppers Jonas Schneider Anselm Haselhoff UQCV 34 8 0 04 Jul 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 27 28 0 17 Jun 2022
COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition M. Tellamekala Shahin Amiriparian Björn W. Schuller Elisabeth André T. Giesbrecht M. Valstar 23 25 0 12 Jun 2022
Low-Degree Multicalibration Parikshit Gopalan Michael P. Kim M. Singhal Shengjia Zhao FaML UQCV 22 37 0 02 Mar 2022
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation Volodymyr Kuleshov Shachi Deshpande UQCV BDL 30 33 0 14 Dec 2021
Online Calibrated and Conformal Prediction Improves Bayesian Optimization Shachi Deshpande Charles Marx Volodymyr Kuleshov 13 7 0 08 Dec 2021
$f$ -Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception Dhaivat Bhatt Kaustubh Mani Dishank Bansal Krishna Murthy Jatavallabhula Hanju Lee Liam Paull UQCV 23 5 0 28 Sep 2021
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling Fabian Küppers Jan Kronenberger Jonas Schneider Anselm Haselhoff UQCV BDL 19 8 0 21 Sep 2021
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration Shengjia Zhao Michael P. Kim Roshni Sahoo Tengyu Ma Stefano Ermon 20 55 0 12 Jul 2021
Flexible Model Aggregation for Quantile Regression Rasool Fakoor Tae-Soo Kim Jonas W. Mueller Alexander J. Smola R. Tibshirani 19 19 0 26 Feb 2021
X-CAL: Explicit Calibration for Survival Analysis Mark Goldstein Xintian Han A. Puli A. Perotte Rajesh Ranganath 31 37 0 13 Jan 2021
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 8 21 0 05 May 2020
PAC-Bayes meta-learning with implicit task-specific posteriors Cuong C. Nguyen Thanh-Toan Do G. Carneiro BDL 31 7 0 05 Mar 2020
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 21 29 0 28 Sep 2019
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference Cuong C. Nguyen Thanh-Toan Do G. Carneiro OOD BDL UQCV 19 54 0 27 Jul 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015