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Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification

18 November 2020

Youngseog Chung

Papers citing "Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification"

50 / 56 papers shown

Title
Individualised Counterfactual Examples Using Conformal Prediction Intervals James M. Adams Gesine Reinert Lukasz Szpruch Carsten Maple Andrew Elliott 32 0 0 28 May 2025
Adapting GT2-FLS for Uncertainty Quantification: A Blueprint Calibration Strategy Yusuf Guven T. Kumbasar 86 0 0 09 Apr 2025
Probabilistic Neural Networks (PNNs) with t-Distributed Outputs: Adaptive Prediction Intervals Beyond Gaussian Assumptions Farhad Pourkamali-Anaraki OOD UQCV 123 0 0 16 Mar 2025
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks Eirik Høyheim Lars Skaaret-Lund Solve Sæbø A. Hubin UQCV BDL 98 0 0 13 Mar 2025
Forecasting Local Ionospheric Parameters Using Transformers D. J. Alford-Lago C. Curtis Alexander T. Ihler Katherine A. Zawdie Douglas P. Drob 90 0 0 24 Feb 2025
Tube Loss: A Novel Approach for Prediction Interval Estimation and probabilistic forecasting Pritam Anand Tathagata Bandyopadhyay Suresh Chandra 118 2 0 08 Dec 2024
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks Dingyi Zhuang Chonghe Jiang Yunhan Zheng Shenhao Wang Jinhua Zhao UQCV 137 0 0 12 Oct 2024
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks Dingyi Zhuang Yuheng Bu Guang Wang Shenhao Wang Jinhua Zhao BDL 80 1 0 13 Sep 2024
Towards certifiable AI in aviation: landscape, challenges, and opportunities Hymalai Bello Daniel Geißler L. Ray Stefan Muller-Divéky Peter Muller Shannon Kittrell Mengxi Liu Bo Zhou Paul Lukowicz 85 1 0 13 Sep 2024
Beyond the Norms: Detecting Prediction Errors in Regression Models A. Altieri Marco Romanelli Georg Pichler F. Alberge Pablo Piantanida 85 0 0 11 Jun 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 470 3 0 05 Jun 2024
Conformal Depression Prediction Yonghong Li Shan Qu Xiuzhuang Zhou 72 2 0 29 May 2024
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models R. Sukthanker Arber Zela B. Staffler Aaron Klein Lennart Purucker Jorg K. H. Franke Frank Hutter ELM 103 4 0 16 May 2024
A Hybrid Probabilistic Battery Health Management Approach for Robust Inspection Drone Operations Jokin Alcibar J. Aizpurua E. Zugasti Oier Penagarikano 55 1 0 24 Apr 2024
Probabilistic Calibration by Design for Neural Network Regression Victor Dheur Souhaib Ben Taieb 187 4 0 18 Mar 2024
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts H. Bui Anqi Liu OOD BDL UQCV 192 4 0 07 Mar 2024
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning Alex C. Stutts Danilo Erricolo Theja Tulabandhula A. R. Trivedi EDL UQCV 92 0 0 11 Feb 2024
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction Ziqi Ma Kamyar Azizzadenesheli A. Anandkumar 83 8 0 02 Feb 2024
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation Tomoharu Iwata Atsutoshi Kumagai BDL UQCV 78 1 0 13 Dec 2023
Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity Pascal Pernot 78 11 0 12 Sep 2023
Benchmarks and Custom Package for Electrical Load Forecasting Zhixian Wang Qingsong Wen Chaoli Zhang Liang Sun Leandro Von Krannichfeldt Yi Wang AI4TS 85 4 0 14 Jul 2023
Understanding Pathologies of Deep Heteroskedastic Regression Eliot Wong-Toi Alex Boyd Vincent Fortuin Stephan Mandt UQCV 69 3 0 29 Jun 2023
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression Victor Dheur Souhaib Ben Taieb BDL 185 14 0 05 Jun 2023
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu Huazhu Fu Qiufeng Wang Q. Hu 100 21 0 02 Jun 2023
Parity Calibration Youngseog Chung Aaron M. Rumack Chirag Gupta 83 2 0 29 May 2023
Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods Shang Liu Zhongze Cai Xiaocheng Li 43 4 0 20 May 2023
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier Aditya Challa Snehanshu Saha S. Dhavala UQCV 74 2 0 25 Apr 2023
Conformalized Unconditional Quantile Regression Ahmed Alaa Zeshan Hussain David Sontag 79 9 0 04 Apr 2023
Uncertainty Propagation in Node Classification Zhao Xu Carolin (Haas) Lawrence Ammar Shaker Raman Siarheyeu BDL UQCV 138 2 0 03 Apr 2023
Adaptive Modeling of Uncertainties for Traffic Forecasting Ying Wu Yongchao Ye Adnan Zeb James Jianqiao Yu Ziyi Wang AI4TS 91 7 0 16 Mar 2023
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts P. Pernot 86 6 0 13 Mar 2023
Lightweight, Uncertainty-Aware Conformalized Visual Odometry Alex C. Stutts Danilo Erricolo Theja Tulabandhula A. R. Trivedi UQCV 110 11 0 03 Mar 2023
Likelihood Annealing: Fast Calibrated Uncertainty for Regression Uddeshya Upadhyay Jae Myung Kim Cordelia Schmidt Bernhard Schölkopf Zeynep Akata BDL UQCV 93 1 0 21 Feb 2023
How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts? Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV 66 12 0 07 Feb 2023
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information Benedikt Heidrich Kaleb Phipps Oliver Neumann Marian Turowski Ralf Mikut V. Hagenmeyer AI4TS BDL 61 2 0 06 Feb 2023
Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification Cameron J Gruich Varun Madhavan Yixin Wang B. Goldsmith 54 11 0 06 Feb 2023
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning Wenxuan Ma Xing Yan Kun Zhang UQCV 66 0 0 24 Dec 2022
Ensemble Multi-Quantiles: Adaptively Flexible Distribution Prediction for Uncertainty Quantification Xing Yan Yonghua Su Wenxuan Ma UQCV 95 2 0 26 Nov 2022
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis Yuxin Xiao Paul Pu Liang Umang Bhatt Willie Neiswanger Ruslan Salakhutdinov Louis-Philippe Morency 253 98 0 10 Oct 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies Willie Neiswanger Lantao Yu Shengjia Zhao Chenlin Meng Stefano Ermon UQCV 97 11 0 04 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 109 3 0 23 Sep 2022
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks Uddeshya Upadhyay Shyamgopal Karthik Yanbei Chen Massimiliano Mancini Zeynep Akata UQCV BDL 105 23 0 14 Jul 2022
Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness Saeid Asgari Taghanaki A. Gholami Fereshte Khani Kristy Choi Linh-Tam Tran Ran Zhang Aliasghar Khani 70 0 0 04 Jul 2022
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection Fabian Küppers Jonas Schneider Anselm Haselhoff UQCV 89 8 0 04 Jul 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip Torr P. Dokania UQCV 104 36 0 29 Jun 2022
Modular Conformal Calibration Charles Marx Shengjia Zhao Willie Neiswanger Stefano Ermon 66 16 0 23 Jun 2022
Achieving Risk Control in Online Learning Settings Shai Feldman Liran Ringel Stephen Bates Yaniv Romano 157 30 0 18 May 2022
Better Uncertainty Calibration via Proper Scores for Classification and Beyond Sebastian G. Gruber Florian Buettner UQCV 83 50 0 15 Mar 2022
Classifier Calibration: A survey on how to assess and improve predicted class probabilities Telmo de Menezes e Silva Filho Hao Song Miquel Perelló Nieto Raúl Santos-Rodríguez Meelis Kull Peter A. Flach 186 85 0 20 Dec 2021
Calibrated Multiple-Output Quantile Regression with Representation Learning Shai Feldman Stephen Bates Yaniv Romano 210 36 0 02 Oct 2021