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.
Automatic interpretable sales forecasting for R
Experiments with experimental rule-based models to go along with imodels.
Code and simulations using biologically annotated neural networks
Explainable AI: From Simple Rules to Complex Generative Models
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.
Predicting categories of scientific papers with advanced machine learning techniques involving class imbalance in multi-label data and explainable machine learning.
Python implementation of TRANSACT, a tool to transfer non-linear predictors of drug response from model systems to tumors.
Rule covering for interpretation and boosting
High precision anchor black box explanation algorithm
Simple implementations of Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP) in JAX
Web based interpretability tool for LLMs using Huggingface and Inseq
Low-dimensional Interpretable Kernels with Conic Discriminant Functions for Classification
Implementing text classification algorithms using the 20 newsgroups datasets, with python
Optimizing Mind static website v1
The nnsight website, which explains and documents the open-source nnsight API
Code for Evaluating the Interpretability of Generative Models by Interactive Reconstruction
Enfoque Estadístico del Aprendizaje - Trabajo práctico - Análisis exploratorio y interpretabilidad de modelos de regresión
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