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Search results for explainable ai interpretable deep learning
explainable-ai
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interpretable-deep-learning
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18 search results found
Pytorch Grad Cam
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8,723
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Path_explain
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134
A repository for explaining feature attributions and feature interactions in deep neural networks.
Xaience
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100
All about explainable AI, algorithmic fairness and more
Deep Explanation Penalization
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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
Prototree
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46
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
Self_critical_vqa
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37
Code for NeurIPS 2019 paper ``Self-Critical Reasoning for Robust Visual Question Answering''
Shapleyexplanationnetworks
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36
Implementation of the paper "Shapley Explanation Networks"
Relative_attributing_propagation
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18
Interpreting DNNs, Relative attributing propagation
Xai
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16
Genetic programming method for explaining complex black-box models
Pipnet
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15
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Label Free Xai
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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'.
Malaria Detection Using Deep Learning Techniques
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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
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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.
Shapley_valuation
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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]
St Protopnet
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6
[ICCV 2023] Learning Support and Trivial Prototypes for Interpretable Image Classification
Deepcoda
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6
Deep learning for personalized interpretability for compositional health data
Timex
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6
Time series explainability via self-supervised model behavior consistency
Ccnn
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5
Comprehensible Convolutional Neural Networks via Guided Concept Learning
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1-18 of 18 search results
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