Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift

29 October 2018

Stephan Günnemann

Papers citing "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift"

26 / 26 papers shown

Title
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts M. Zarlenga Gabriele Dominici Pietro Barbiero Z. Shams M. Jamnik KELM 57 0 0 24 Apr 2025
Monitor and Recover: A Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical Systems Vivian Lin Insup Lee 27 0 0 18 Apr 2025
In-Situ Fine-Tuning of Wildlife Models in IoT-Enabled Camera Traps for Efficient Adaptation Mohammad Mehdi Rastikerdar Jin Huang Hui Guan Deepak Ganesan 54 0 0 12 Sep 2024
Learning Run-time Safety Monitors for Machine Learning Components Ozan Vardal Richard Hawkins Colin Paterson Chiara Picardi Daniel Omeiza Lars Kunze Ibrahim Habli 25 0 0 23 Jun 2024
Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection Eduardo Dadalto F. Alberge Pierre Duhamel Pablo Piantanida OODD 21 0 0 23 Jun 2024
Open-Source Drift Detection Tools in Action: Insights from Two Use Cases Rieke Müller Mohamed Abdelaal Davor Stjelja 9 0 0 29 Apr 2024
Out-of-Distribution Detection using Maximum Entropy Coding M. Abolfazli Mohammad Zaeri Amirani Anders Høst-Madsen June Zhang A. Bratincsák OOD 19 0 0 25 Apr 2024
SupEuclid: Extremely Simple, High Quality OoD Detection with Supervised Contrastive Learning and Euclidean Distance J. Haas OODD 8 0 0 21 Aug 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 20 3 0 20 Aug 2023
Addressing caveats of neural persistence with deep graph persistence Leander Girrbach Anders Christensen Ole Winther Zeynep Akata A. Sophia Koepke GNN 11 1 0 20 Jul 2023
Rectifying Group Irregularities in Explanations for Distribution Shift Adam Stein Yinjun Wu Eric Wong Mayur Naik 20 1 0 25 May 2023
DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models Vivian Lin Kuk Jin Jang Souradeep Dutta Michele Caprio O. Sokolsky Insup Lee OOD 21 6 0 20 Feb 2023
Testing for context-dependent changes in neural encoding in naturalistic experiments Ye Chen Carl Harris Xiaoyu Ma Zheng Li Francisco Câmara Pereira Charles Y.Zheng 24 0 0 17 Nov 2022
Explanation Shift: Detecting distribution shifts on tabular data via the explanation space Carlos Mougan Klaus Broelemann Gjergji Kasneci T. Tiropanis Steffen Staab FAtt 25 7 0 22 Oct 2022
Calibrated Selective Classification Adam Fisch Tommi Jaakkola Regina Barzilay 11 16 0 25 Aug 2022
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness Vincent Jeanselme Maria De-Arteaga Zhe Zhang Jessica Barrett Brian D. M. Tom FaML 31 11 0 13 Aug 2022
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners Anthony Sicilia Katherine Atwell Malihe Alikhani Seong Jae Hwang BDL 29 9 0 12 Jul 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra A. Madry 9 88 0 29 Jun 2022
Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network M. T. Huyut Andrei Velichko 11 32 0 20 May 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 30 11 0 13 May 2022
Active Learning Over Multiple Domains in Natural Language Tasks Shayne Longpre Julia Reisler E. G. Huang Yi Lu Andrew J. Frank Nikhil Ramesh Chris DuBois OOD 17 13 0 01 Feb 2022
RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice Michael Fitzke Conrad Stack Andre Dourson Rodrigo M. B. Santana Diane U Wilson L. Ziemer Arjun Soin M. Lungren Paul Fisher Mark Parkinson LM&MA MedIm 11 5 0 09 Nov 2021
Natural Attribute-based Shift Detection Jeonghoon Park Jimin Hong Radhika Dua Daehoon Gwak Yixuan Li Jaegul Choo E. Choi OOD 17 3 0 18 Oct 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 105 349 0 04 Oct 2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing Sindhu C. M. Gowda Shalmali Joshi Haoran Zhang Marzyeh Ghassemi CML 11 8 0 27 Aug 2021
Combining p-values via averaging V. Vovk Ruodu Wang FedML 52 205 0 20 Dec 2012