431 Open source projects that are alternatives of or similar to hierarchical-dnn-interpretations

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

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

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

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

[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.

Fit interpretable models. Explain blackbox machine learning.

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

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

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Papers about explainability of GNNs

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

Predictive AI layer for existing databases.

Adaptive, interpretable wavelets across domains (NeurIPS 2021)

Data generator for Arena - interactive XAI dashboard

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

Model interpretability and understanding for PyTorch

For calculating global feature importance using Shapley values.

Collection of NLP model explanations and accompanying analysis tools

XAI - An eXplainability toolbox for machine learning

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

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

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

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

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

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

Molecular Explanation Generator

Open and collaborative content from leet hackers!

README for Rekcurd projects

Visit our website for more Mobile and Web applications

Revisiting Rainbow

Flexible data structures for complex machine learning datasets.

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

Examples of Data Science projects and Artificial Intelligence use cases

双色球+大乐透彩票AI预测

Python PMML scoring library

Racing game AI

📒 Experiment tracking tool and model registry

Normal & height maps generation from single pictures

Just add pull requests to this repo and stand a chance to win a limited edition Hacktoberfest T-shirt.

No description or website provided.

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

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

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

OpenAI's Gym written in pure Rust for blazingly fast performance

🧪 Learning Neural Generative Dynamics for Molecular Conformation Generation (ICLR 2021)

Towards Reverse-Engineering Black-Box Neural Networks, ICLR'18

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

Distributed SQL Engine in Python using Dask

Leetcode using AI

Subscribe to this GitHub repo to access the latest tech talks, tech demos, learning materials & modules, and developer community updates!

Enabling easy statistical significance testing for deep neural networks.

Code for Neural Inverse Knitting: From Images to Manufacturing Instructions

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.

speaker diarization system using an LSTM

A curated list of datasets, publically available for machine learning research in the area of manufacturing

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.

📃Language Model based sentences scoring library

Coalton is (supposed to be) a dialect of ML embedded in Common Lisp.

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).

OSDG is an open-source tool that maps and connects activities to the UN Sustainable Development Goals (SDGs) by identifying SDG-relevant content in any text. The tool is available online at www.osdg.ai. API access available for research purposes.