Topic: explainable-machine-learning Goto Github
Some thing interesting about explainable-machine-learning
Some thing interesting about explainable-machine-learning
explainable-machine-learning,XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.
User: 11301858
Home Page: https://xaisuite.wordpress.com
explainable-machine-learning,How to use SHAP to interpret machine learning models
User: afairless
Home Page: https://afairless.com/shap-tutorial/
explainable-machine-learning,A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
User: akarasman
explainable-machine-learning,Predicting categories of scientific papers with advanced machine learning techniques involving class imbalance in multi-label data and explainable machine learning.
User: alfagama
explainable-machine-learning,A new benchmark for graph neural network explainer methods
User: alirezadizaji
explainable-machine-learning,BBBP Explainer is a code to generate structural alerts of blood-brain barrier penetrating and non-penetrating drugs using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from BBBP dataset.
User: andresilvapimentel
explainable-machine-learning,t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections
User: angeloschatzimparmpas
Home Page: https://doi.org/10.1109/TVCG.2020.2986996
explainable-machine-learning,Getting explanations for predictions made by black box models.
User: datatrigger
Home Page: https://blog.vlgdata.io/post/interpretable_machine_learning_shap/
explainable-machine-learning,Graduate research project in computer vision and deep learning explainability
User: dlambert13
explainable-machine-learning,XLabel: An Explainable Data Labeling Assistant
User: donlapark
explainable-machine-learning,Reading list for adversarial perspective and robustness in deep reinforcement learning.
User: ezgikorkmaz
explainable-machine-learning,A Novel Optimization Objective for Explainable and Customizable Learning of Multi-Classifiers
User: flaai
explainable-machine-learning,An R package providing functions for interpreting and distilling machine learning models
Organization: forestry-labs
Home Page: https://forestry-labs.github.io/distillML
explainable-machine-learning,Implementation of Model-Agnostic Graph Explainability Technique from Scratch in PyTorch
User: fork123aniket
explainable-machine-learning,[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"
User: hkuds
Home Page: https://dl.acm.org/doi/10.1145/3583780.3614871
explainable-machine-learning,Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images
User: hungntt
explainable-machine-learning,Counterfactual SHAP: a framework for counterfactual feature importance
Organization: jpmorganchase
explainable-machine-learning,Counterfactual Shapley Additive Explanation: Experiments
Organization: jpmorganchase
explainable-machine-learning,Measuring galaxy environmental distance scales with GNNs and explainable ML models
User: jwuphysics
Home Page: https://arxiv.org/abs/2402.07995
explainable-machine-learning,This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of gravelly soils. This model is developed using LightGBM and SHAP.
User: kaushikjas10
Home Page: https://doi.org/10.1016/j.compgeo.2023.106051
explainable-machine-learning,This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of soils. This model is developed using XGBoost and SHAP.
User: kaushikjas10
Home Page: https://doi.org/10.1016/j.soildyn.2022.107662
explainable-machine-learning,Use of Machine Learning and Deep Learning Algorithms to recommend best clinical options to health professionals in South Africa
User: kavuur
explainable-machine-learning,Final year project, exploring the field of quantum machine learning.
User: lukepower01
explainable-machine-learning,A baseline genetic algorithm for the discovery of counterfactuals, implemented in Python for ease of use and heavily leveraging NumPy for speed.
User: marcovirgolin
explainable-machine-learning,Repo of the paper "On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations"
User: marcovirgolin
explainable-machine-learning,Explainable Ensemble Trees
User: massimoaria
Home Page: https://massimoaria.github.io/e2tree/
explainable-machine-learning,This repository consists the supplemental materials of the paper "Decomposition of Expected Goal Models: Aggregated SHAP Values for Analyzing Scoring Potential of Player/Team".
User: mcavs
explainable-machine-learning,[Frontiers in AI Journal] Implementation of the paper "Interpreting Vision and Language Generative Models with Semantic Visual Priors"
User: michelecafagna26
explainable-machine-learning,📍 Interactive Studio for Explanatory Model Analysis
Organization: modeloriented
Home Page: https://doi.org/10.1007/s10618-023-00924-w
explainable-machine-learning,Explainable Machine Learning in Survival Analysis
Organization: modeloriented
Home Page: https://modeloriented.github.io/survex
explainable-machine-learning,Predicting whether an African country will be in recession or not with advanced machine learning techniques involving class imbalance, cost-sensitive learning and explainable machine learning
User: orestislampridis
explainable-machine-learning,Explaining sentiment classification by generating synthetic exemplars and counter-exemplars in the latent space
User: orestislampridis
explainable-machine-learning,Code for the School of AI challenge "Explainable AI for Wildfire Forecasting", sponsored by Pi School to help NOA, the National Observatory of Athens, work with Explainable Deep Learning for Wildfire Forecasting.
Organization: pischool
explainable-machine-learning,A Python library for Secure and Explainable Machine Learning
Organization: pralab
Home Page: https://secml.readthedocs.io
explainable-machine-learning,Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN
User: prclibo
explainable-machine-learning,This module extends the kernel SHAP method (as introduced by Lundberg and Lee (2017)) which is local in nature, to a method that computes global SHAP values.
User: roye10
explainable-machine-learning,This repository contains the Business Intelligence insights generated as part of the final project challenge for the DTU Data Science course 42578: Advanced Business Analytics
User: seby-sbirna
explainable-machine-learning,This repository contains a comprehensive implementation of gradient descent for linear regression, including visualizations and comparisons with ordinary least squares (OLS) regression. It also includes an additional implementation for multiple linear regression using gradient descent.
User: shreyansh-2003
explainable-machine-learning,Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
User: szandala
Home Page: https://pypi.org/project/torchprism
explainable-machine-learning,The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)
User: tangli-udel
Home Page: https://tangli0305.github.io/
explainable-machine-learning,Explanation-guided boosting of machine learning evasion attacks.
User: um-dsp
explainable-machine-learning,Ths repo has the list of Interesting Literature in the domain of XAI
User: umberh
explainable-machine-learning,A collection of algorithms of counterfactual explanations.
User: wangyongjie-ntu
Home Page: https://cfai.readthedocs.io/en/latest/
explainable-machine-learning,XMLX GitHub configuration
Organization: xmlx-io
Home Page: https://github.com/xmlx-io
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