Local explanations with uncertainty 💐!

🌊 Online machine learning in Python

GLIME is a post-hoc explanation method which is proved to be much more stable and faithful than LIME.

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Explaining the output of machine learning models with more accurately estimated Shapley values

Bayesian Adaptive Spline Surfaces for flexible and automatic regression

A clean and robust Pytorch implementation of PPO on Discrete action space

A collection of research materials on explainable AI/ML

IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control

Explaining the output of machine learning models with more accurately estimated Shapley values

Learning how to implement GA and NSGA-II for job shop scheduling problem in python

Data Science in Manufacturing 製造資料科學