LENS Project

Minimal starting point for rapid prototyping interactive Human-AI tools

Experiments with experimental rule-based models to go along with imodels.

XAI-Analytics is a tool that opens the black-box of machine learning. It helps the user to understand the decision-making process of machine learning models.

Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data

Code of experiments implemented in the paper "Explainability of Predictive Process Monitoring results: Techniques, Experiments and Lessons Learned", comparing XAI methods at different granularities (global/local) with different settings on predictive process monitoring outcomes using process mining event logs

A little lab of learning algorithms (in LUA). Less XAI, but better

In this article, the factors affecting BERT's transferability is explained through visualizations

Official Website of https://github.com/tamlhp/awesome-privex

A scoring system for explainability

Official implementation for Plan-of-SQLs or POS

HTML version of the book Feature Engineering & Selection for Explainable Models A Second Course for Data Scientists

Website for health data science at KDD 2021

Show case for modelStudio based on ⚽⚽⚽FIFA 20 ⚽⚽⚽

DVDPong: Retro DVD screensaver meets Pong! Bounce for points, chase corner hits with confetti, play right from your browser. Built with Grok 3 by xAI.

This project poses a new methodology for assessing and improving sequential concept bottleneck models (CBMs). The research undertaken in this project builds upon the model proposed by Grange et al., of which I was one of the co-authors.

XAI를 활용한 서울 카페 리뷰 분석

This Tower of Hanoi Game Prototype is an attempt at explaining Q-learning and Reinforcement Learning Principles to People in an Intuitive and Interactive Way

Conway's Game of Life is sequential, here high-dimensional states are projected into the two-dimensional space, and connected, furthermore, meta-data is added to create interactive 2D visualizations.