| Name | Version | Summary | date |
| bhad |
0.2.6 |
Bayesian Histogram-based Anomaly Detection |
2025-01-26 00:33:00 |
| arize |
7.32.0 |
A helper library to interact with Arize AI APIs |
2025-01-23 23:03:09 |
| explainerdashboard |
0.4.8 |
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models. |
2024-12-29 21:23:35 |
| oracle-automlx |
24.4.1 |
Automated Machine Learning with Explainability |
2024-12-03 09:04:22 |
| arize-slim |
0.1.1 |
A helper library to interact with Arize AI APIs |
2024-10-15 18:15:30 |
| maskinversion-torch |
1.1 |
MaskInversion |
2024-10-14 17:31:02 |
| lux-explainer |
1.3.2 |
Universal Local Rule-based Explainer |
2024-09-19 10:34:25 |
| plenoptic |
1.1.0 |
Python library for model-based stimulus synthesis. |
2024-09-16 19:27:06 |
| tsproto |
0.3.0 |
Post-host prototype-based explanations with rules for time-series classifiers |
2024-09-11 11:58:25 |
| hippo-nn |
0.1.0 |
HIPPO explainability toolkit for computational pathology. |
2024-09-06 11:54:06 |
| antakia |
0.4.6 |
AI made Xplainable |
2024-05-13 17:21:50 |
| goalEDP |
0.0.7 |
Library for processing goal-oriented agents. Processing is done on an event-driven mechanism. Events are saved to be used by explanation generating methods. |
2024-03-20 18:58:08 |