interpretability · GitHub Topics

shap / shap

#计算机科学#A game theoretic approach to explain the output of any machine learning model.

interpretability 机器学习深度学习 gradient-boosting shap shapley explainability

Jupyter Notebook 24 k

3 天前

EthicalML / awesome-production-machine-learning

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

机器学习 mlops interpretability explainability responsible-ai 深度学习 machine-learning-operations ml-ops ml-operations privacy-preserving privacy-preserving-machine-learning data-mining production-machine-learning Awesome Lists

18.6 k

15 天前

jacobgil / pytorch-grad-cam

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

深度学习 PyTorch grad-cam visualizations interpretability interpretable-ai interpretable-deep-learning score-cam class-activation-maps vision-transformers explainable-ai xai image-classification 机器学习 object-detection 机器视觉 explainable-ml

Python 11.77 k

2 个月前

interpretml / interpret

#计算机科学#Fit interpretable models. Explain blackbox machine learning.

机器学习 interpretability gradient-boosting blackbox scikit-learn xai interpretml interpretable-machine-learning interpretable-ai transparency interpretable-ml explainable-ml explainability bias 人工智能 explainable-ai differential-privacy

C++ 6.53 k

6 天前

pytorch / captum

Model interpretability and understanding for PyTorch

interpretability interpretable-ai interpretable-ml feature-importance feature-attribution

Python 5.26 k

2 天前

tensorflow / lucid

#计算机科学#A collection of infrastructure and tools for research in neural network interpretability.

Tensorflow interpretability 可视化机器学习 colab Jupyter Notebook

Jupyter Notebook 4.69 k

2 年前

jphall663 / awesome-machine-learning-interpretability

#Awesome#A curated list of awesome responsible machine learning resources.

fairness xai interpretability transparency 机器学习数据科学 Python R Awesome Lists machine-learning-interpretability interpretable-machine-learning interpretable-ml interpretable-ai explainable-ml ai-safety privacy-enhancing-technologies privacy-preserving-machine-learning

3.8 k

5 天前

stellargraph / stellargraph

#计算机科学#StellarGraph - Machine Learning on Graphs

graphs 机器学习 graph-convolutional-networks networkx geometric-deep-learning saliency-map interpretability heterogeneous-networks graph-neural-networks graph-analysis gcn graph-data Python 深度学习数据科学

Python 3.01 k

1 年前

MAIF / shapash

#计算机科学#🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Python 机器学习 explainability explainable-ml transparency ethical-artificial-intelligence shap lime interpretability

Jupyter Notebook 2.9 k

4 天前

SeldonIO / alibi

#计算机科学#Algorithms for explaining machine learning models

机器学习 explanations interpretability counterfactual xai

Python 2.52 k

1 个月前

frgfm / torch-cam

#计算机科学#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)

PyTorch Python 深度学习 cnn gradcam saliency-map interpretability interpretable-deep-learning score-cam grad-cam

Python 2.21 k

10 天前

chaoyanghe / Awesome-Federated-Learning

#计算机科学#FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

federated-learning 机器学习 neural-architecture-search transfer-learning continual-learning semi-supervised-learning 隐私 interpretability 机器视觉

1.96 k

3 年前

google-deepmind / penzai

A JAX research toolkit for building, editing, and visualizing neural networks.

fine-tuning interpretability jax neural-networks 可视化

Python 1.79 k

2 个月前

ramprs / grad-cam

#计算机科学#[ICCV 2017] Torch code for Grad-CAM

grad-cam interpretability convolutional-neural-networks 深度学习 heatmap

Lua 1.57 k

3 年前

microsoft / responsible-ai-toolbox

#计算机科学#Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libr...