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Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
v1v2 (latest)

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

6 June 2019
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift"

50 / 1,062 papers shown
Title
Towards Robust Model Evolution with Algorithmic Recourse
Hao-Tsung Yang
Jie Gao
Bo-Yi Liu
Zhi-Xuan Liu
80
0
0
12 Mar 2025
Certainly Bot Or Not? Trustworthy Social Bot Detection via Robust Multi-Modal Neural Processes
Qi Wu
Yingguang Yang
Hao Liu
Hao Peng
Buyun He
Yutong Xia
Yong Liao
AAML
129
0
0
11 Mar 2025
PostHoc FREE Calibrating on Kolmogorov Arnold Networks
Wenhao Liang
Wei Emma Zhang
Lin Yue
Miao Xu
Olaf Maennel
Weitong Chen
105
0
0
03 Mar 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
Hyunsu Kim
G. Nam
Chulhee Yun
Hongseok Yang
Juho Lee
BDLUQCV
103
0
0
02 Mar 2025
Ranking pre-trained segmentation models for zero-shot transferability
Joshua Talks
Anna Kreshuk
426
0
0
01 Mar 2025
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
556
1
0
28 Feb 2025
Similarity-Distance-Magnitude Universal Verification
Similarity-Distance-Magnitude Universal Verification
Allen Schmaltz
UQCVAAML
552
0
0
27 Feb 2025
Incremental Learning with Repetition via Pseudo-Feature Projection
Incremental Learning with Repetition via Pseudo-Feature Projection
Benedikt Tscheschner
Eduardo Veas
Marc Masana
CLL
76
0
0
27 Feb 2025
A calibration test for evaluating set-based epistemic uncertainty representations
A calibration test for evaluating set-based epistemic uncertainty representations
Mira Jürgens
Thomas Mortier
Eyke Hüllermeier
Viktor Bengs
Willem Waegeman
103
1
0
22 Feb 2025
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization
Behraj Khan
Behroz Mirza
Nouman Durrani
T. Syed
139
0
0
18 Feb 2025
The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation
The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation
Martin Mundt
Anaelia Ovalle
Felix Friedrich
A Pranav
Subarnaduti Paul
Manuel Brack
Kristian Kersting
William Agnew
720
0
0
05 Feb 2025
GDO: Gradual Domain Osmosis
GDO: Gradual Domain Osmosis
Zixi Wang
Yubo Huang
470
0
0
31 Jan 2025
Bayesian Optimization with Preference Exploration by Monotonic Neural Network Ensemble
Bayesian Optimization with Preference Exploration by Monotonic Neural Network Ensemble
Hanyang Wang
Juergen Branke
Matthias Poloczek
226
0
0
30 Jan 2025
Technical report on label-informed logit redistribution for better domain generalization in low-shot classification with foundation models
Technical report on label-informed logit redistribution for better domain generalization in low-shot classification with foundation models
Behraj Khan
T. Syed
502
1
0
29 Jan 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang
Keivan K1 Shariatmadar
Shireen Kudukkil Manchingal
Fabio Cuzzolin
David Moens
Hans Hallez
UQCVBDL
270
14
0
28 Jan 2025
Reliable Text-to-SQL with Adaptive Abstention
Reliable Text-to-SQL with Adaptive Abstention
Kaiwen Chen
Yueting Chen
Xiaohui Yu
Nick Koudas
RALM
88
2
0
18 Jan 2025
Can Bayesian Neural Networks Explicitly Model Input Uncertainty?
Can Bayesian Neural Networks Explicitly Model Input Uncertainty?
Matias Valdenegro-Toro
Marco Zullich
BDLPERUQCVUD
488
0
0
14 Jan 2025
Testing Human-Hand Segmentation on In-Distribution and Out-of-Distribution Data in Human-Robot Interactions Using a Deep Ensemble Model
Testing Human-Hand Segmentation on In-Distribution and Out-of-Distribution Data in Human-Robot Interactions Using a Deep Ensemble Model
R. Jalayer
Yuxin Chen
Masoud Jalayer
C. Orsenigo
Masayoshi Tomizuka
34
0
0
13 Jan 2025
Uncertainty Guarantees on Automated Precision Weeding using Conformal Prediction
Uncertainty Guarantees on Automated Precision Weeding using Conformal Prediction
P. Melki
Lionel Bombrun
Boubacar Diallo
Jérôme Dias
Jean-Pierre da Costa
74
0
0
13 Jan 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
Jiayi Huang
Sangwoo Park
Osvaldo Simeone
252
2
0
03 Jan 2025
Pretraining with random noise for uncertainty calibration
Pretraining with random noise for uncertainty calibration
Jeonghwan Cheon
Se-Bum Paik
OnRL
180
2
0
23 Dec 2024
Test-Time Alignment via Hypothesis Reweighting
Test-Time Alignment via Hypothesis Reweighting
Yoonho Lee
Jonathan Williams
Henrik Marklund
Archit Sharma
E. Mitchell
Anikait Singh
Chelsea Finn
141
5
0
11 Dec 2024
Detecting Discrepancies Between AI-Generated and Natural Images Using
  Uncertainty
Detecting Discrepancies Between AI-Generated and Natural Images Using Uncertainty
Jun Nie
Yonggang Zhang
Tongliang Liu
Y. Cheung
Bo Han
Xinmei Tian
UQCV
133
1
0
08 Dec 2024
Detecting Fake News on Social Media: A Novel Reliability Aware
  Machine-Crowd Hybrid Intelligence-Based Method
Detecting Fake News on Social Media: A Novel Reliability Aware Machine-Crowd Hybrid Intelligence-Based Method
Yidong Chai
Kangwei Shi
Jiaheng Xie
Chunli Liu
Yuanchun Jiang
Yezheng Liu
113
0
0
07 Dec 2024
Enhancing Zero-shot Chain of Thought Prompting via Uncertainty-Guided Strategy Selection
Shanu Kumar
Saish Mendke
Karody Lubna Abdul Rahman
Santosh Kurasa
Parag Agrawal
Sandipan Dandapat
LLMAGLRM
138
3
0
30 Nov 2024
Customer Lifetime Value Prediction with Uncertainty Estimation Using
  Monte Carlo Dropout
Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout
Xinzhe Cao
Yadong Xu
Xiaofeng Yang
118
0
0
24 Nov 2024
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image Classification
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image Classification
Sara Pohland
Claire Tomlin
UQCV
203
1
0
22 Nov 2024
Improving OOD Generalization of Pre-trained Encoders via Aligned
  Embedding-Space Ensembles
Improving OOD Generalization of Pre-trained Encoders via Aligned Embedding-Space Ensembles
Shuman Peng
Arash Khoeini
Sharan Vaswani
Martin Ester
149
0
0
20 Nov 2024
Improving self-training under distribution shifts via anchored
  confidence with theoretical guarantees
Improving self-training under distribution shifts via anchored confidence with theoretical guarantees
Taejong Joo
Diego Klabjan
UQCV
104
0
0
01 Nov 2024
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy
  Minimization of CKA
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA
David Smerkous
Qinxun Bai
Fuxin Li
BDL
119
1
0
31 Oct 2024
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers
Lam Nguyen Tung
Steven Cho
Xiaoning Du
Neelofar Neelofar
Valerio Terragni
Stefano Ruberto
Aldeida Aleti
538
2
0
30 Oct 2024
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Arthur Pignet
Chiara Regniez
John Klein
182
1
0
30 Oct 2024
Domain Adaptation with a Single Vision-Language Embedding
Domain Adaptation with a Single Vision-Language Embedding
Mohammad Fahes
Tuan-Hung Vu
Andrei Bursuc
Patrick Pérez
Raoul de Charette
VLM
71
0
0
28 Oct 2024
Ensembling Finetuned Language Models for Text Classification
Ensembling Finetuned Language Models for Text Classification
Sebastian Pineda Arango
Maciej Janowski
Lennart Purucker
Arber Zela
Frank Hutter
Josif Grabocka
73
0
0
25 Oct 2024
Theoretical Limitations of Ensembles in the Age of Overparameterization
Theoretical Limitations of Ensembles in the Age of Overparameterization
Niclas Dern
John P. Cunningham
Geoff Pleiss
BDLUQCV
90
1
0
21 Oct 2024
The Disparate Benefits of Deep Ensembles
The Disparate Benefits of Deep Ensembles
Kajetan Schweighofer
Adrián Arnaiz-Rodríguez
Sepp Hochreiter
Nuria Oliver
FedML
86
1
0
17 Oct 2024
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Johan Hatleskog
Kostas Alexis
3DPC
105
2
0
14 Oct 2024
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene
  Semantic Segmentation
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation
Hanieh Shojaei
Qianqian Zou
Max Mehltretter
UQCV
78
0
0
11 Oct 2024
Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble
  Deep Kernel Learning Model
Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model
Yonghang Zhou
Hongyi Zhu
Yidong Chai
Yuanchun Jiang
Yezheng Liu
AAML
108
0
0
10 Oct 2024
Evaluating Computational Pathology Foundation Models for Prostate Cancer
  Grading under Distribution Shifts
Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts
Fredrik K. Gustafsson
Mattias Rantalainen
OODMedIm
83
1
0
09 Oct 2024
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs
Ruijia Niu
D. Wu
Rose Yu
Yi-An Ma
124
2
0
09 Oct 2024
Predicting Battery Capacity Fade Using Probabilistic Machine Learning
  Models With and Without Pre-Trained Priors
Predicting Battery Capacity Fade Using Probabilistic Machine Learning Models With and Without Pre-Trained Priors
Michael J. Kenney
Katerina G. Malollari
Sergei V. Kalinin
M. Ziatdinov
BDL
58
0
0
08 Oct 2024
Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces
Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces
Vahid Hashemi
Jan Křetínský
Sabine Rieder
Torsten Schön
Jan Vorhoff
67
0
0
08 Oct 2024
Probing Language Models on Their Knowledge Source
Probing Language Models on Their Knowledge Source
Zineddine Tighidet
Andrea Mogini
Jiali Mei
Benjamin Piwowarski
Patrick Gallinari
KELM
80
1
0
08 Oct 2024
Improving Predictor Reliability with Selective Recalibration
Improving Predictor Reliability with Selective Recalibration
Thomas P. Zollo
Zhun Deng
Jake C. Snell
T. Pitassi
Richard Zemel
OOD
72
0
0
07 Oct 2024
Regularized Neural Ensemblers
Regularized Neural Ensemblers
Sebastian Pineda Arango
Maciej Janowski
Lennart Purucker
Arber Zela
Frank Hutter
Josif Grabocka
UQCV
95
0
0
06 Oct 2024
Distribution Guided Active Feature Acquisition
Distribution Guided Active Feature Acquisition
Yang Li
Junier Oliva
71
0
0
04 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty
  Quantification in Deep Learning
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
Nils Lehmann
Jakob Gawlikowski
Adam J. Stewart
Vytautas Jancauskas
Stefan Depeweg
Eric T. Nalisnick
N. Gottschling
110
0
0
04 Oct 2024
Probabilistic road classification in historical maps using synthetic
  data and deep learning
Probabilistic road classification in historical maps using synthetic data and deep learning
Dominik J. Mühlematter
Sebastian Schweizer
Chenjing Jiao
Xue Xia
M. Heitzler
L. Hurni
64
0
0
03 Oct 2024
Toward a Holistic Evaluation of Robustness in CLIP Models
Toward a Holistic Evaluation of Robustness in CLIP Models
Weijie Tu
Weijian Deng
Tom Gedeon
VLM
74
5
0
02 Oct 2024
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