Using sequential drift detection to test the API economy
- Samuel Ackerman
- Parijat Dube
- et al.
- 2021
- arXiv
Paper
Publications
84 results for AI Testing
Online Adaptation of Parameters using GRU-based Neural Network with BO for Accurate Driving Model
- Zhanhong Yang
- Satoshi Masuda
- et al.
- 2021
- SIGSPATIAL GIS 2021
Conference paperDetecting model drift using polynomial relations
- Eliran Roffe
- Samuel Ackerman
- et al.
- 2022
- AAAI 2022
Workshop paperDynamic 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
PaperWorkflow Provenance in the Lifecycle of Scientific Machine Learning
- Renan Francisco Santos Souza
- Leonardo Guerreiro Azevedo
- et al.
- 2021
- CCPE
PaperA Guided Approach Towards Complex Chaos Selection, Prioritisation and Injection
- Ojaswa Sharma
- Mudit Verma
- et al.
- 2022
- CLOUD 2022
Conference paperMachine Learning Model Drift Detection Via Weak Data Slices
- Samuel Ackerman
- Parijat Dube
- et al.
- 2021
- ICSE 2021
Workshop paperTesting Framework for Black-box AI Models
- Aniya Aggarwal
- Samiulla Shaikh
- et al.
- 2021
- ICSE 2021
Demo paperGenerate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text
- Nishtha Madaan
- Inkit Padhi
- et al.
- 2021
- AAAI 2021
Conference paperVerifying individual fairness in machine learning models
- Philips George John
- Deepak Vijaykeerthy
- et al.
- 2020
- UAI 2020
Conference paper