On Calibration and Out-of-domain Generalization

20 February 2021

Papers citing "On Calibration and Out-of-domain Generalization"

42 / 42 papers shown

Title
Partial Transportability for Domain Generalization Kasra Jalaldoust Alexis Bellot Elias Bareinboim OOD 77 5 0 30 Mar 2025
FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups Géraldin Nanfack Eugene Belilovsky 59 0 0 10 Feb 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference Jiayi Huang Sangwoo Park Osvaldo Simeone 108 2 0 03 Jan 2025
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments Gaojie Jin Ronghui Mu Xinping Yi Xiaowei Huang Lijun Zhang 67 0 0 01 Jul 2024
Learning Invariant Causal Mechanism from Vision-Language Models Changwen Zheng Siyu Zhao Xingyu Zhang Jiangmeng Li Changwen Zheng Jingyao Wang CML BDL VLM 45 0 0 24 May 2024
Data Augmentations for Improved (Large) Language Model Generalization Amir Feder Yoav Wald Claudia Shi S. Saria David M. Blei OOD CML 32 7 0 19 Oct 2023
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration Hiroki Naganuma Ryuichiro Hataya Kotaro Yoshida Ioannis Mitliagkas OODD 95 1 0 17 Jul 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 18 56 0 01 Jun 2023
An Invariant Learning Characterization of Controlled Text Generation Carolina Zheng Claudia Shi Keyon Vafa Amir Feder David M. Blei OOD 38 8 0 31 May 2023
Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution Jiahao Chen Bingyue Su 32 11 0 13 Apr 2023
A principled approach to model validation in domain generalization Boyang Lyu Thuan Q. Nguyen matthias. scheutz Prakash Ishwar Shuchin Aeron 38 2 0 02 Apr 2023
DOMINO: Domain-aware Loss for Deep Learning Calibration Skylar E. Stolte Kyle Volle A. Indahlastari Alejandro Albizu A. Woods Kevin Brink Matthew Hale R. Fang MedIm 13 1 0 10 Feb 2023
Beyond In-Domain Scenarios: Robust Density-Aware Calibration Christian Tomani Futa Waseda Yuesong Shen Daniel Cremers UQCV 34 4 0 10 Feb 2023
Domain Generalization with Correlated Style Uncertainty Zheyu Zhang Bin Wang Debesh Jha Ugur Demir Ulas Bagci OOD 38 5 0 20 Dec 2022
Learning useful representations for shifting tasks and distributions Jianyu Zhang Léon Bottou OOD 34 13 0 14 Dec 2022
Malign Overfitting: Interpolation Can Provably Preclude Invariance Yoav Wald G. Yona Uri Shalit Y. Carmon 17 5 0 28 Nov 2022
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research J. Bornschein Alexandre Galashov Ross Hemsley Amal Rannen-Triki Yutian Chen ... Angeliki Lazaridou Yee Whye Teh Andrei A. Rusu Razvan Pascanu MarcÁurelio Ranzato OOD VLM AI4TS 39 16 0 15 Nov 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity Dennis Ulmer J. Frellsen Christian Hardmeier 189 22 0 20 Oct 2022
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis Yuxin Xiao Paul Pu Liang Umang Bhatt W. Neiswanger Ruslan Salakhutdinov Louis-Philippe Morency 175 86 0 10 Oct 2022
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective Yao Zhu YueFeng Chen Xiaodan Li Kejiang Chen Yuan He Xiang Tian Bo Zheng Yao-wu Chen Qingming Huang AAML 33 58 0 09 Oct 2022
A Comprehensive Review of Trends, Applications and Challenges In Out-of-Distribution Detection Navid Ghassemi E. F. Ersi AAML OODD 23 4 0 26 Sep 2022
Calibrated Selective Classification Adam Fisch Tommi Jaakkola Regina Barzilay 29 16 0 25 Aug 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 60 71 0 19 Jul 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift Ananya Kumar Tengyu Ma Percy Liang Aditi Raghunathan UQCV OODD OOD 42 38 0 18 Jul 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 38 29 0 06 Jul 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 126 32 0 04 Jul 2022
When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen Ruibin Xiong Zhiming Ma Yanyan Lan OOD CML 27 20 0 29 Jun 2022
Learning to Detect with Constant False Alarm Rate Tzvi Diskin Uri Okun A. Wiesel 18 8 0 12 Jun 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni Dylan J. Foster Dipendra Kumar Misra A. Krishnamurthy John Langford OffRL 29 25 0 09 Jun 2022
The Missing Invariance Principle Found -- the Reciprocal Twin of Invariant Risk Minimization Dongsung Huh A. Baidya OOD 28 8 0 29 May 2022
Estimating Model Performance on External Samples from Their Limited Statistical Characteristics T. El-Hay C. Yanover OOD 13 1 0 28 Feb 2022
Robust Hybrid Learning With Expert Augmentation Antoine Wehenkel Jens Behrmann Hsiang Hsu Guillermo Sapiro Gilles Louppe and J. Jacobsen 26 8 0 08 Feb 2022
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization Alexandre Ramé Corentin Dancette Matthieu Cord OOD 40 204 0 07 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond Amir Feder Katherine A. Keith Emaad A. Manzoor Reid Pryzant Dhanya Sridhar ... Roi Reichart Margaret E. Roberts Brandon M Stewart Victor Veitch Diyi Yang CML 41 234 0 02 Sep 2021
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations Stephen R. Pfohl Haoran Zhang Yizhe Xu Agata Foryciarz Marzyeh Ghassemi N. Shah OOD 29 22 0 27 Aug 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration Yezhen Wang Bo-wen Li Tong Che Kaiyang Zhou Ziwei Liu Dongsheng Li UQCV 22 47 0 27 Jul 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey Anton Van Den Hengel 25 87 0 12 May 2021
Generalizing to Unseen Domains: A Survey on Domain Generalization Jindong Wang Cuiling Lan Chang-Shu Liu Yidong Ouyang Tao Qin Wang Lu Yiqiang Chen Wenjun Zeng Philip S. Yu OOD 54 1,170 0 02 Mar 2021
PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains Eyal Ben-David Nadav Oved Roi Reichart VLM OOD 17 88 0 24 Feb 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 198 125 0 04 Jan 2021
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 243 289 0 17 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020