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

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

29 October 2018

Stephan Rabanser

Stephan Günnemann

Zachary Chase Lipton

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

11 / 61 papers shown

Title
GitTables: A Large-Scale Corpus of Relational Tables Madelon Hulsebos cCaugatay Demiralp Paul T. Groth LMTD 26 83 0 14 Jun 2021
InFlow: Robust outlier detection utilizing Normalizing Flows Nishant Kumar Pia Hanfeld Michael Hecht Michael Bussmann Stefan Gumhold Nico Hoffmann OODD OOD TPM 29 4 0 10 Jun 2021
MLDemon: Deployment Monitoring for Machine Learning Systems Antonio A. Ginart Martin Jinye Zhang James Zou 54 18 0 28 Apr 2021
Failing Conceptually: Concept-Based Explanations of Dataset Shift Maleakhi A. Wijaya Dmitry Kazhdan B. Dimanov M. Jamnik 9 7 0 18 Apr 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 25 108 0 26 Feb 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends Q. Rahman Peter Corke Feras Dayoub OOD 29 51 0 05 Jan 2021
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 22 65 0 30 Nov 2020
Ethical Machine Learning in Health Care Irene Y. Chen Emma Pierson Sherri Rose Shalmali Joshi Kadija Ferryman Marzyeh Ghassemi AILaw 20 371 0 22 Sep 2020
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics V. Ramasesh Ethan Dyer M. Raghu CLL 24 173 0 14 Jul 2020
Monitoring and explainability of models in production Janis Klaise A. V. Looveren Clive Cox G. Vacanti Alexandru Coca 35 49 0 13 Jul 2020
Combining p-values via averaging V. Vovk Ruodu Wang FedML 65 205 0 20 Dec 2012