#计算机科学#Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
翻译 - 在Pytorch中为CNN和视觉变压器实现了许多类激活图方法。包括Grad-CAM,Grad-CAM ++,Score-CAM,Ablation-CAM和XGrad-CAM
#计算机科学#Fit interpretable models. Explain blackbox machine learning.
翻译 - 拟合可解释的模型。说明黑匣子机器学习。
Model interpretability and understanding for PyTorch
翻译 - PyTorch的模型可解释性和理解
#Awesome#A curated list of awesome responsible machine learning resources.
A collection of research materials on explainable AI/ML
#计算机科学#Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
#计算机科学#H2O.ai Machine Learning Interpretability Resources
#计算机科学#Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms...
#计算机科学#Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
#计算机科学#PyTorch Explain: Interpretable Deep Learning in Python.
#计算机科学#Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, pro...
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classif...
Explainable AI in Julia.
All about explainable AI, algorithmic fairness and more
#计算机科学#Material related to my book Intuitive Machine Learning. Some of this material is also featured in my new book Synthetic Data and Generative AI.
#计算机科学#Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
#Awesome#A curated list of awesome academic research, books, code of ethics, data sets, institutes, maturity models, newsletters, principles, podcasts, reports, tools, regulations and standards related to Resp...
#计算机科学#Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
#自然语言处理#XAI based human-in-the-loop framework for automatic rule-learning.