Tensorflow tutorial for various Deep Neural Network visualization techniques

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

A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

Pytorch implementation of various neural network interpretability methods

使用LSTM及股票因子数据预测未来收益，使用LRP(layer-wise relevance propagation)增强网络可解释性

A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).

We predict religion from personal names only.

Cyber Security AI Dashboard

A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.

xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology

Explainable AI in Julia.

An XAI library that helps to explain AI models in a really quick & easy way

ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.

eirspo official branch of odoo for better localization and openness

[ECCV 2022: Oral] In this work, we discover that color is a crtical transferable forensic feature (T-FF) in universal detectors for detecting CNN-generated images.

Repository for the 'best student paper award' winning paper at the IEEE 35th International Symposium on Computer Based Medical Systems (CBMS 2022), Exploring LRP and Grad-CAM visualization to interpret multi-label-multi-class pathology prediction using chest radiography, Mahbub Ul Alam, Jón Rúnar Baldvinsson and Yuxia Wang. https://doi.org/10.11…