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53 search results found

Pytorch Grad Cam ⭐ 8,723

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Torch Cam ⭐ 1,695

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)

Deeplift ⭐ 584

Public facing deeplift repo

Awesome Trustworthy Deep Learning ⭐ 254

A curated list of trustworthy deep learning papers. Daily updating...

Understanding Nn ⭐ 222

Tensorflow tutorial for various Deep Neural Network visualization techniques

[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

Hatexplain ⭐ 152

Can we use explanations to improve hate speech models? Our paper accepted at AAAI 2021 tries to explore that question.

Path_explain ⭐ 134

A repository for explaining feature attributions and feature interactions in deep neural networks.

Visual Attribution ⭐ 117

Pytorch Implementation of recent visual attribution methods for model interpretability

Gradcam_plus_plus Pytorch ⭐ 102

A Simple pytorch implementation of GradCAM and GradCAM++

Xaience ⭐ 100

All about explainable AI, algorithmic fairness and more

Deepaffinity ⭐ 80

Protein-compound affinity prediction through unified RNN-CNN

Attributionpriors ⭐ 75

Tools for training explainable models using attribution priors.

Deep Explanation Penalization ⭐ 74

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

Layerwise Relevance Propagation ⭐ 51

Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers

Prototree ⭐ 46

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

Multislice PHATE for tensor embeddings

Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks

Nn_interpretability ⭐ 37

Pytorch implementation of various neural network interpretability methods

Self_critical_vqa ⭐ 37

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

Shapleyexplanationnetworks ⭐ 36

Implementation of the paper "Shapley Explanation Networks"

Cross Modal Transformer ⭐ 32

Official repository of cross-modal transformer for interpretable automatic sleep stage classification. https://arxiv.org/abs/2208.06991

Cnn Units In Nlp ⭐ 26

✂️ Repository for our ICLR 2019 paper: Discovery of Natural Language Concepts in Individual Units of CNNs

Devise Keras ⭐ 22

Interpretable Image Search by Priyam Tejaswin and Akshay Chawla

Attentivechrome ⭐ 20

NeurIPS17: [AttentiveChrome] Attend and Predict: Using Deep Attention Model to Understand Gene Regulation by Selective Attention on Chromatin

Relative_attributing_propagation ⭐ 18

Interpreting DNNs, Relative attributing propagation

Rl_singing_voice ⭐ 18

Unsupervised Representation Learning for Singing Voice Separation

Genetic programming method for explaining complex black-box models

∂B nets: learning discrete, boolean-valued functions by gradient descent

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

Redunet_paper ⭐ 15

Official Implementation of Deep Networks from the Principle of Rate Reduction (2021)

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

In-silico Saturation Mutagenesis implementation with 10x or more speedup for certain architectures.

Towards Interpretable Deep Metric Learning with Structural Matching

Towards Visually Explaining Video Understanding Networks With Perturbation ⭐ 11

Attribution (or visual explanation) methods for understanding video classification networks. Demo codes for WACV2021 paper: Towards Visually Explaining Video Understanding Networks with Perturbation.

Label Free Xai ⭐ 10

This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.

Class_selectivity_index ⭐ 9

On the importance of single directions for generalization(Morcos et al, ICLR 2018)

Malaria Detection Using Deep Learning Techniques ⭐ 9

Malaria Parasite Detection using Efficient Neural Ensembles. Malaria, a life threatening disease caused by the bite of the Anopheles mosquito infected with the parasite, has been a major burden towards healthcare for years leading to approximately 400,000 deaths globally every year. This study aims to build an efficient system by applying ensemble techniques based on deep learning to automate the detection of the parasite using whole slide images of thin blood smears.

Explore Deep Network Explainability Using An App ⭐ 8

This repository provides an app for exploring the predictions of an image classification network using several deep learning visualization techniques. Using the app, you can: explore network predictions with occlusion sensitivity, Grad-CAM, and gradient attribution methods, investigate misclassifications using confusion and t-SNE plots, visualize layer activations, and many more techniques to help you understand and explain your deep network’s predictions.

Interpret Lm Knowledge ⭐ 8

Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.

Interpretability Of Machine Learning Visualizations ⭐ 7

Interpretability of Machine Learning-Visualizations

Ecg Diagnosis ⭐ 7

Code and Datasets for the paper "Interpretable deep learning for automatic diagnosis of 12-lead electrocardiogram", published on iScience in 2021.

Visualizations Of The Interpretations Of Cnns ⭐ 7

Using Sensitivity Heatmap, Deconvolution, Guided Backpropagation, Class Activation Mapping, Grad-CAM and Guided Grad-CAM methods to interpret the predictions of different CNN models

St Protopnet ⭐ 6

[ICCV 2023] Learning Support and Trivial Prototypes for Interpretable Image Classification

Transmatcher ⭐ 6

TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification

Deep learning for personalized interpretability for compositional health data

Time series explainability via self-supervised model behavior consistency

Shapley_valuation ⭐ 6

PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuation of Data" by Amirata Ghorbani and James Zou [ICML 2019]

Transformer_anatomy ⭐ 6

Official Pytorch implementation of (Roles and Utilization of Attention Heads in Transformer-based Neural Language Models), ACL 2020

Dynamic Shap Plots ⭐ 5

Enabling interactive plotting of the visualizations from the SHAP project.

ICCV2021 paper: Interpretable Image Recognition by Constructing Transparent Embedding Space (TesNet)

Comprehensible Convolutional Neural Networks via Guided Concept Learning

Clinically-Interpretable Radiomics [MICCAI'22, CMPB'21]

1-53 of 53 search results

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