125 Open source projects that are alternatives of or similar to zennit

Fit interpretable models. Explain blackbox machine learning.

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

Model interpretability and understanding for PyTorch

Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

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

A curated list of awesome machine learning interpretability resources.

Adaptive, interpretable wavelets across domains (NeurIPS 2021)

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Papers about explainability of GNNs

Collection of NLP model explanations and accompanying analysis tools

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

Data generator for Arena - interactive XAI dashboard

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

[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.

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

Visualization tool for Graph Neural Networks

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

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

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

MindsDB server allows you to consume and expose MindsDB workflows, through http.

Molecular Explanation Generator

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

Code for NeurIPS 2019 paper ``Self-Critical Reasoning for Robust Visual Question Answering''

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

Fast approximate Shapley values in R

In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)

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

A lightweight implementation of removal-based explanations for ML models.

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

For calculating global feature importance using Shapley values.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

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

A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.

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

An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.

Visualize BERT's self-attention layers on text classification tasks

Arctos is a museum collections management system

Examples of Data Science projects and Artificial Intelligence use cases

Model verification, validation, and error analysis

Explains machine learning models fast using the Anchor algorithm originally proposed by marcotcr in 2018

Concept Bottleneck Models, ICML 2020

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data

This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.

Variants of Vision Transformer and its downstream tasks

Essential NLP & ML, short & fast pure Python code

⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.

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

NeurIPS 2018. Linear-time model comparison tests.

Implementation of the paper "Shapley Explanation Networks"

A modern approach to author attribution in WordPress.

Official Implementation of Remembering for the Right Reasons (ICLR 2021)

Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020

Machine Learning in one line of code

Machine Learning Finite State Machine Models from Data with Genetic Algorithms

Python library for Ceteris Paribus Plots (What-if plots)

Malware similarity platform with modularity in mind.

official implementation of "Visualization of Convolutional Neural Networks for Monocular Depth Estimation"

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