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Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty
  Quantification
v1v2v3v4 (latest)

Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification

18 November 2020
Youngseog Chung
Willie Neiswanger
I. Char
J. Schneider
    UQCV
ArXiv (abs)PDFHTML

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

50 / 56 papers shown
Title
Individualised Counterfactual Examples Using Conformal Prediction Intervals
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
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
Probabilistic Neural Networks (PNNs) with t-Distributed Outputs: Adaptive Prediction Intervals Beyond Gaussian Assumptions
Farhad Pourkamali-Anaraki
OODUQCV
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
UQCVBDL
98
0
0
13 Mar 2025
Forecasting Local Ionospheric Parameters Using Transformers
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
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
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
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
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
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
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
Conformal Depression Prediction
Yonghong Li
Shan Qu
Xiuzhuang Zhou
70
2
0
29 May 2024
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models
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
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
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
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts
H. Bui
Anqi Liu
OODBDLUQCV
192
4
0
07 Mar 2024
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential
  Reinforcement Learning
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning
Alex C. Stutts
Danilo Erricolo
Theja Tulabandhula
A. R. Trivedi
EDLUQCV
92
0
0
11 Feb 2024
Calibrated Uncertainty Quantification for Operator Learning via
  Conformal Prediction
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
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation
Tomoharu Iwata
Atsutoshi Kumagai
BDLUQCV
78
1
0
13 Dec 2023
Calibration in Machine Learning Uncertainty Quantification: beyond
  consistency to target adaptivity
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
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
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
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
Calibrating Multimodal Learning
Huanrong Zhang
Changqing Zhang
Bing Wu
Huazhu Fu
Qiufeng Wang
Q. Hu
100
21
0
02 Jun 2023
Parity Calibration
Parity Calibration
Youngseog Chung
Aaron M. Rumack
Chirag Gupta
83
2
0
29 May 2023
Distribution-Free Model-Agnostic Regression Calibration via
  Nonparametric Methods
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
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
Conformalized Unconditional Quantile Regression
Ahmed Alaa
Zeshan Hussain
David Sontag
79
9
0
04 Apr 2023
Uncertainty Propagation in Node Classification
Uncertainty Propagation in Node Classification
Zhao Xu
Carolin (Haas) Lawrence
Ammar Shaker
Raman Siarheyeu
BDLUQCV
138
2
0
03 Apr 2023
Adaptive Modeling of Uncertainties for Traffic Forecasting
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
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts
P. Pernot
84
6
0
13 Mar 2023
Lightweight, Uncertainty-Aware Conformalized Visual Odometry
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
Likelihood Annealing: Fast Calibrated Uncertainty for Regression
Uddeshya Upadhyay
Jae Myung Kim
Cordelia Schmidt
Bernhard Schölkopf
Zeynep Akata
BDLUQCV
93
1
0
21 Feb 2023
How Reliable is Your Regression Model's Uncertainty Under Real-World
  Distribution Shifts?
How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?
Fredrik K. Gustafsson
Martin Danelljan
Thomas B. Schon
OODUQCV
66
12
0
07 Feb 2023
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical
  Information
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information
Benedikt Heidrich
Kaleb Phipps
Oliver Neumann
Marian Turowski
Ralf Mikut
V. Hagenmeyer
AI4TSBDL
61
2
0
06 Feb 2023
Clarifying Trust of Materials Property Predictions using Neural Networks
  with Distribution-Specific Uncertainty Quantification
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
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
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
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
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
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
BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
Uddeshya Upadhyay
Shyamgopal Karthik
Yanbei Chen
Massimiliano Mancini
Zeynep Akata
UQCVBDL
105
23
0
14 Jul 2022
Counterbalancing Teacher: Regularizing Batch Normalized Models for
  Robustness
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
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
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
Modular Conformal Calibration
Charles Marx
Shengjia Zhao
Willie Neiswanger
Stefano Ermon
66
16
0
23 Jun 2022
Achieving Risk Control in Online Learning Settings
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
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
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
Calibrated Multiple-Output Quantile Regression with Representation Learning
Shai Feldman
Stephen Bates
Yaniv Romano
210
36
0
02 Oct 2021
12
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