101 Open source projects that are alternatives of or similar to Interpretability By Parts

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Molecular Explanation Generator

Global-Local Capsule Network (GLCapsNet) is a capsule-based architecture able to provide context-based eye fixation prediction for several autonomous driving scenarios, while offering interpretability both globally and locally.

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

Data generator for Arena - interactive XAI dashboard

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

XAI Tutorial for the Explainable AI track in the ALPS winter school 2021

NeurIPS 2018. Linear-time model comparison tests.

Adaptive, interpretable wavelets across domains (NeurIPS 2021)

Collection of NLP model explanations and accompanying analysis tools

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM)

💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)

Model interpretability and understanding for PyTorch

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

A collection of research materials on explainable AI/ML

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

A Python package implementing a new machine learning model for text classification with visualization tools for Explainable AI

A curated list of awesome machine learning interpretability resources.

A game theoretic approach to explain the output of any machine learning model.

📍 Interactive Studio for Explanatory Model Analysis

Layer-wise Relevance Propagation (LRP) for LSTMs

StellarGraph - Machine Learning on Graphs

A curated list of awesome Fairness in AI resources

Pytorch Implementation of recent visual attribution methods for model interpretability

⬛ Python Individual Conditional Expectation Plot Toolbox

Model Agnostics breakDown plots

Awesome Resources for Advanced Computer Vision Topics

Simple Implementation of many GAN models with PyTorch.

PyTorch Implementation of InfoGAN

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

To obtain high resolution face images from CelebA

MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)

Tensorflow implementation of different GANs and their comparisions

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM