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Fit interpretable models. Explain blackbox machine learning.
Created
2019-05-03
3,651 commits to develop branch, last one 2 days ago
Model interpretability and understanding for PyTorch
Created
2019-08-27
1,269 commits to master branch, last one 18 hours ago
A curated list of awesome responsible machine learning resources.
r
xai
python
awesome
fairness
ai-safety
secure-ml
reliable-ai
awesome-list
data-science
transparency
explainable-ml
interpretability
interpretable-ai
interpretable-ml
machine-learning
interpretable-machine-learning
privacy-enhancing-technologies
machine-learning-interpretability
privacy-preserving-machine-learning
Created
2018-06-21
1,248 commits to master branch, last one 11 hours ago
High-Performance Symbolic Regression in Python and Julia
Created
2020-09-14
2,616 commits to master branch, last one 6 days ago
Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/
Created
2018-11-19
35 commits to master branch, last one 4 years ago
This repository has no description...
Created
2017-12-27
86 commits to master branch, last one 4 years ago
Distributed High-Performance Symbolic Regression in Julia
Created
2021-01-14
3,364 commits to master branch, last one 17 days ago
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Created
2018-03-14
169 commits to master branch, last one 2 years ago
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
nlp
xai
data-mining
text-mining
text-labeling
ss3-classifier
interpretability
interpretable-ml
machine-learning
text-classification
early-classification
artificial-intelligence
document-categorization
document-classification
sentence-classification
multilabel-classification
machine-learning-algorithms
natural-language-processing
interpretable-machine-learning
explainable-artificial-intelligence
Created
2019-11-11
404 commits to master branch, last one 2 months ago
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Created
2020-11-10
232 commits to master branch, last one 11 months ago
An Open-Source Library for the interpretability of time series classifiers
Created
2022-08-15
486 commits to main branch, last one 3 months ago
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...
Created
2021-09-30
10 commits to main branch, last one about a year ago
Explainable Machine Learning in Survival Analysis
r
xai
shap
cox-model
r-package
brier-scores
biostatistics
censored-data
time-to-event
cox-regression
explainable-ai
explainable-ml
interpretable-ml
machine-learning
survival-analysis
variable-importance
explanatory-model-analysis
explainable-machine-learning
interpretable-machine-learning
probabilistic-machine-learning
Created
2022-08-31
480 commits to main branch, last one 9 months ago
Optimal Sparse Decision Trees
Created
2019-06-05
28 commits to master branch, last one about a year ago
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Created
2023-03-24
15 commits to main branch, last one about a year ago
[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
Created
2023-10-09
86 commits to main branch, last one 4 months ago
A PyTorch implementation of constrained optimization and modeling techniques
Created
2023-11-08
76 commits to main branch, last one 10 months ago