An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.
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Updated
May 23, 2024 - TeX
An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.
Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI and Human-Centered AI.
Fit interpretable models. Explain blackbox machine learning.
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
As part of the Explainable AI Toolkit (XAITK), XAITK-Saliency is an open source, explainable AI framework for visual saliency algorithm interfaces and implementations, built for analytics and autonomy applications.
A Python library for explainable AI using approximate reasoning
This repository contains the Python scripts that I have written and run to execute a series of analytic model developments using datasets taken from the book "The Elements of Statistical Elements" by Hastie, Tibshirani, Friedman
moDel Agnostic Language for Exploration and eXplanation
My github page
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
Interpretable Machine Learning via Rule Extraction
[ICLR 2024] Official implementation of the paper "GNNBoundary"
[ICLR 2023] Official implementation of the paper "GNNInterpreter"
A project focusing on binary classification using Explainable Artificial Intelligence (XAI) methods, specifically SHAP (SHapley Additive exPlanations), and Grid Search for hyperparameter tuning. The project utilizes EfficientNetV2-B0 architecture on the Cat VS Dog dataset.
A solid foundational understanding of XAI, primarily emphasizing how XAI methodologies can expose latent biases in datasets and reveal valuable insights.
High-Performance Symbolic Regression in Python and Julia
Concise summaries of key papers in responsible AI.
👋 Xplique is a Neural Networks Explainability Toolbox
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