Monitoring and explainability of models in production

Monitoring and explainability of models in production

13 July 2020

Papers citing "Monitoring and explainability of models in production"

9 / 9 papers shown

Title
Estimating Model Performance Under Covariate Shift Without Labels Jakub Bialek W. Kuberski Nikolaos Perrakis Albert Bifet 20 2 0 16 Jan 2024
Monitoring Machine Learning Models: Online Detection of Relevant Deviations Florian Heinrichs 14 2 0 26 Sep 2023
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record Conor K. Corbin R. Maclay Aakash Acharya Sreedevi Mony Soumya Punnathanam Rahul Thapa N. Kotecha N. Shah Jonathan H. Chen 8 17 0 11 Mar 2023
Desiderata for next generation of ML model serving Sherif Akoush Andrei Paleyes A. V. Looveren Clive Cox 13 5 0 26 Oct 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 16 23 0 16 Apr 2022
CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI Arjun Soin J. Merkow Jin Long Joseph Paul Cohen Smitha Saligrama Stephen Kaiser Steven Borg I. Tarapov M. Lungren OOD 45 15 0 06 Feb 2022
Ensembling Shift Detectors: an Extensive Empirical Evaluation Simona Maggio L. Dreyfus-Schmidt AI4TS 25 3 0 28 Jun 2021
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 25 623 0 01 Jul 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016