Deep Insight And Neural Network Analysis
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Updated
Jun 26, 2024 - Jupyter Notebook
Deep Insight And Neural Network Analysis
This repo contains the code of my Master's Thesis. Specifically, it consists in exploring different techniques(Explanable AI, Physics Informed NN, ...) to perform State Estimation
Choregraphe App for Pepper robots to enable them to tell a scripted story specified in a Google spreadsheet.
Data science projects at Aboitiz
Explainable Artificial Intelligence through Contextual Importance and Utility
Awesome Heart Sound Analysis - A Survey
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
moDel Agnostic Language for Exploration and eXplanation
🤖 Making AI understandable and transparent, enhancing trust and accountability.
Local interpretability for survival models
Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images
Local Universal Rule-based Explanations
Trustworthy AI/ML course by Professor Birhanu Eshete, University of Michigan, Dearborn.
Counterfactuals: Take the uncertainty out of your machine learning models
Endocrine Disruption Explainer is a code to generate structural alerts of endocrine disruption of chemcial compounds using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from TOX-21, EDC, and EDKB-FDA datasets.
This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima
Official Implementation of TMLR's paper: "TabCBM: Concept-based Interpretable Neural Networks for Tabular Data"
An Open-Source Library for the interpretability of time series classifiers
This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of gravelly soils. This model is developed using LightGBM and SHAP.
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