Detecting model drift using polynomial relations
- Eliran Roffe
- Samuel Ackerman
- et al.
- 2022
- AAAI 2022
Publications
62 results for AI Testing
Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription
- Shashanka Ubaru
- Lior Horesh
- et al.
- 2021
- Journal of Biomedical Informatics
Workflow Provenance in the Lifecycle of Scientific Machine Learning
- Renan Francisco Santos Souza
- Leonardo Guerreiro Azevedo
- et al.
- 2021
- CCPE
A Guided Approach Towards Complex Chaos Selection, Prioritisation and Injection
- Ojaswa Sharma
- Mudit Verma
- et al.
- 2022
- CLOUD 2022
Machine Learning Model Drift Detection Via Weak Data Slices
- Samuel Ackerman
- Parijat Dube
- et al.
- 2021
- ICSE 2021
Testing Framework for Black-box AI Models
- Aniya Aggarwal
- Samiulla Shaikh
- et al.
- 2021
- ICSE 2021
Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text
- Nishtha Madaan
- Inkit Padhi
- et al.
- 2021
- AAAI 2021
Verifying individual fairness in machine learning models
- Philips George John
- Deepak Vijaykeerthy
- et al.
- 2020
- UAI 2020
Quality Management of Machine Learning Systems
- 2020
- AAAI 2020
Reliable Counterfactual Explanations for Autoencoder based Anomalies
- Swastik Haldar
- Philips George John
- et al.
- 2021
- CODS-COMAD 2021