#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。
#Awesome#A curated list of awesome responsible machine learning resources.
#计算机科学#moDel Agnostic Language for Exploration and eXplanation
#计算机科学#Generate Diverse Counterfactual Explanations for any machine learning model.
翻译 - 为任何机器学习模型生成多样的反事实解释。
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
#计算机科学#OmniXAI: A Library for eXplainable AI
#计算机科学#[HELP REQUESTED] Generalized Additive Models in Python
Interesting resources related to XAI (Explainable Artificial Intelligence)
#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...
#自然语言处理#A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI )
#学习与技能提升#📍 Interactive Studio for Explanatory Model Analysis
💡 Adversarial attacks on explanations and how to defend them
#计算机科学#PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Concept Bottleneck Models, ICML 2020
#计算机科学#🕵️♂️ Interpreting Convolutional Neural Network (CNN) Results.
#计算机科学#🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease
#计算机科学#[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.