(Almost) Provable Error Bounds Under Distribution Shift via Disagreement
Discrepancy

(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy

Neural Information Processing Systems (NeurIPS), 2023

1 June 2023

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Papers citing "(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy"

9 / 9 papers shown

Title
ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction Han Yu Kehan Li Dongbai Li Yue He Xingxuan Zhang Peng Cui OODD 314 0 0 31 Oct 2025
Knowledge Distillation of Uncertainty using Deep Latent Factor Model Sehyun Park Jongjin Lee Yunseop Shin Ilsang Ohn Yongdai Kim UQCV BDL 329 0 0 22 Oct 2025
Monitoring Risks in Test-Time Adaptation Mona Schirmer Metod Jazbec C. A. Naesseth Eric T. Nalisnick TTA 456 2 0 11 Jul 2025
On Continuous Monitoring of Risk Violations under Unknown ShiftConference on Uncertainty in Artificial Intelligence (UAI), 2025 Alexander Timans Rajeev Verma Eric T. Nalisnick C. A. Naesseth 147 2 0 19 Jun 2025
ODD: Overlap-aware Estimation of Model Performance under Distribution ShiftConference on Uncertainty in Artificial Intelligence (UAI), 2025 Aayush Mishra Anqi Liu 136 1 0 17 Jun 2025
Adapting to Online Distribution Shifts in Deep Learning: A Black-Box ApproachInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025 Dheeraj Baby Boran Han Shuai Zhang Cuixiong Hu Yuyang Wang Yu Wang OOD 232 1 0 09 Apr 2025
Source-Free Domain-Invariant Performance PredictionEuropean Conference on Computer Vision (ECCV), 2024 Ekaterina Khramtsova Mahsa Baktashmotlagh Guido Zuccon Xi Wang Mathieu Salzmann UQCV 214 1 0 05 Aug 2024
Beyond Top-Class Agreement: Using Divergences to Forecast Performance under Distribution Shift Mona Schirmer Dan Zhang Eric T. Nalisnick 121 0 0 13 Dec 2023
One-Shot Strategic Classification Under Unknown CostsInternational Conference on Machine Learning (ICML), 2023 Elan Rosenfeld Nir Rosenfeld OffRL 306 10 0 05 Nov 2023