Visualization toolkit for neural networks in PyTorch! Demo -->
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Updated
Sep 21, 2023 - HTML
Visualization toolkit for neural networks in PyTorch! Demo -->
All about explainable AI, algorithmic fairness and more
Explain a black-box module in natural language.
Code and simulations using biologically annotated neural networks
Rule covering for interpretation and boosting
Experiments with experimental rule-based models to go along with imodels.
Code for Evaluating the Interpretability of Generative Models by Interactive Reconstruction
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.
Explainable AI: From Simple Rules to Complex Generative Models
Implementing text classification algorithms using the 20 newsgroups datasets, with python
Simple implementations of Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP) in JAX
High precision anchor black box explanation algorithm
Python implementation of TRANSACT, a tool to transfer non-linear predictors of drug response from model systems to tumors.
The nnsight website, which explains and documents the open-source nnsight API
Automatic interpretable sales forecasting for R
Low-dimensional Interpretable Kernels with Conic Discriminant Functions for Classification
Web based interpretability tool for LLMs using Huggingface and Inseq
The website for NDIF, the National Deep Inference Fabric
Optimizing Mind static website v1
Predicting categories of scientific papers with advanced machine learning techniques involving class imbalance in multi-label data and explainable machine learning.
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