Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
-
Updated
Mar 9, 2023 - Python
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A curated list of awesome machine learning interpretability resources.
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Public facing deeplift repo
Tensorflow tutorial for various Deep Neural Network visualization techniques
A Simple pytorch implementation of GradCAM and GradCAM++
[ECCV 2020] QAConv: Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting, and [CVPR 2022] GS: Graph Sampling Based Deep Metric Learning
A repository for explaining feature attributions and feature interactions in deep neural networks.
Can we use explanations to improve hate speech models? Our paper accepted at AAAI 2021 tries to explore that question.
Pytorch Implementation of recent visual attribution methods for model interpretability
Protein-compound affinity prediction through unified RNN-CNN
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
A curated list of trustworthy deep learning papers. Daily updating...
Tools for training explainable models using attribution priors.
All about explainable AI, algorithmic fairness and more
Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers
Pytorch implementation of various neural network interpretability methods
[ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching
Interpreting DNNs, Relative attributing propagation
Implementation of the paper "Shapley Explanation Networks"
Add a description, image, and links to the interpretable-deep-learning topic page so that developers can more easily learn about it.
To associate your repository with the interpretable-deep-learning topic, visit your repo's landing page and select "manage topics."