#
interpretable-ai
Here are 33 public repositories matching this topic...
A curated list of awesome machine learning interpretability resources.
python
data-science
machine-learning
data-mining
awesome
r
awesome-list
transparency
fairness
accountability
interpretability
interpretable-deep-learning
interpretable-ai
interpretable-ml
explainable-ml
xai
fatml
interpretable-machine-learning
iml
machine-learning-interpretability
-
Updated
Aug 19, 2020
Model interpretability and understanding for PyTorch
-
Updated
Aug 19, 2020 - Python
data-science
machine-learning
interpretable-ai
interpretable-ml
explainable-ai
xai
interpretable-machine-learning
-
Updated
Jul 9, 2020 - Python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
python
data-science
machine-learning
data-mining
h2o
gradient-boosting-machine
transparency
decision-tree
fairness
lime
accountability
interpretability
interpretable-ai
interpretable-ml
xai
fatml
interpretable
interpretable-machine-learning
iml
machine-learning-interpretability
-
Updated
Aug 11, 2020 - Jupyter Notebook
H2O.ai Machine Learning Interpretability Resources
python
data-science
machine-learning
data-mining
h2o
xgboost
transparency
jupyter-notebooks
fairness
accountability
interpretability
interpretable-ai
interpretable-ml
explainable-ml
mli
xai
fatml
interpretable-machine-learning
iml
machine-learning-interpretability
-
Updated
May 22, 2020 - Jupyter Notebook
ExplainX is a fast, light-weight, and scalable explainable AI framework for data scientists to explain and debug any black-box model.
python
machine-learning
ai
artificial-intelligence
trust
transparency
blackbox
bias
interpretability
explainable-artificial-intelligence
interpretable-ai
explainable-ai
xai
interpretable-machine-learning
explainx
-
Updated
Aug 19, 2020 - Jupyter Notebook
All about explainable AI, algorithmic fairness and more
interpretability
explainable-artificial-intelligence
interpretable-deep-learning
interpretable-ai
explainable-ai
explainable-ml
interpretable-machine-learning
-
Updated
Jul 20, 2020
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
machine-learning
transparency
fairness
accountability
interpretability
interpretable-ai
explainable-ai
explainability
-
Updated
Aug 12, 2020 - Python
Code for NeurIPS 2019 paper ``Self-Critical Reasoning for Robust Visual Question Answering''
-
Updated
Sep 9, 2019 - Python
In this part, i've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
machine-learning
computer-vision
deep-learning
grad-cam
mnist
gradients
backpropagation
blackbox
saliency-map
cifar-10
smoothgrad
guided-backpropagation
interpretable-ai
explainable-ai
integrated-gradients
evaluate-models
-
Updated
Mar 4, 2020 - Jupyter Notebook
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
data-science
machine-learning
data-mining
transparency
fairness
accountability
interpretability
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
xai
fatml
interpretable-machine-learning
iml
machine-learning-interpretability
fairness-ai
fairness-ml
-
Updated
Nov 19, 2019 - TeX
A toolkit for interpreting and analyzing neural networks (vision)
deep-learning
artificial-intelligence
neural-networks
image-optimization
artistic-style-transfer
neural-style-transfer
interpretable-ai
interpretable-machine-learning
-
Updated
Jul 28, 2020 - Jupyter Notebook
list
machine-learning
awesome
awesome-list
interpretability
adversarial-learning
adversarial-machine-learning
adversarial-examples
explainable-artificial-intelligence
adversarial-attacks
interpretable-deep-learning
interpretable-ai
explainable-ai
explainable-ml
xai
interpretable-machine-learning
iml
adversarial-defense
-
Updated
Jul 30, 2020
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
python
data-science
machine-learning
data-mining
gradient-boosting-machine
transparency
decision-trees
fairness
lime
accountability
interpretability
interpretable-ai
interpretable-ml
xai
fatml
interpretable
interpretable-machine-learning
iml
machine-learning-interpretability
-
Updated
Jul 15, 2020 - Jupyter Notebook
Article for Special Edition of Information: Machine Learning with Python
python
data-science
machine-learning
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
xai
fatml
fairness-testing
interpretable-machine-learning
iml
machine-learning-interpretability
fairness-ai
fairness-ml
-
Updated
May 6, 2020 - Jupyter Notebook
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
python
data-science
machine-learning
data-mining
transparency
interpretability
interpretable-ai
interpretable-ml
explainable-ml
xai
fatml
interpretable-machine-learning
iml
machine-learning-interpretability
-
Updated
Dec 7, 2018 - TeX
A collection of research materials on explainable AI/ML
-
Updated
Aug 16, 2020
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
machine-learning
transparency
aaai
interpretability
rule-based
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
xai
interpretable-machine-learning
iml
machine-learning-interpretability
explainability
rule-sets
interpretml
transparent-ml
-
Updated
Feb 19, 2020 - Python
Explainability of Deep Learning Models
clustering
rct
uncertainty
intervention
causality
causal-inference
concept-extraction
interpretability
interpretable-ai
explainable-ai
gradcam
ablation
explainability
dissection
joint-analysis
activation-maximization
-
Updated
Aug 14, 2020 - Python
Concept activation vectors for Keras
interpretability
explainable-artificial-intelligence
interpretable-deep-learning
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
interpretable-machine-learning
explainability
-
Updated
Jan 28, 2020 - Python
Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions
caffe
ssd
object-detection
interpretable-deep-learning
interpretable-ai
explainable-ai
explainable-ml
e2x
-
Updated
Nov 22, 2018 - C++
Interpretable AI with Safeguard AI (paper study, implement-code review)
-
Updated
Nov 11, 2018
A scoring system for explainability
-
Updated
Jan 28, 2020 - Python
Overview of machine learning interpretation techniques and their implementations
python
data-science
machine-learning
transparency
interpretation
interpretability
model-interpretation
interpretable-ai
interpretable-ml
mli
xai
interpretable-machine-learning
machine-learning-interpretability
interpretable-classifcation
-
Updated
Aug 22, 2019 - Jupyter Notebook
ProtoTorch is a PyTorch-based Python toolbox for bleeding-edge research in prototype-based machine learning algorithms.
-
Updated
Aug 4, 2020 - Python
explainable and interpretable methods for AI and data science
-
Updated
May 2, 2020 - Jupyter Notebook
Optimizing Mind static website v1
machine-learning
ai
machine-learning-algorithms
ml
artificial-intelligence
artificial-neural-networks
artificial-general-intelligence
machinelearning
machine-learning-api
artificial-neural-network
machine-intelligence
artificial-intelligence-algorithms
interpretability
artifical-intelligense
explainable-artificial-intelligence
illuminated-ai
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
-
Updated
Oct 4, 2018 - HTML
A python library to agnostically explain multi-label black-box classifiers (tabular data)
python3
explanation
interpretability
multilabel
multilabel-classification
explainable-artificial-intelligence
interpretable-ai
interpretable-ml
explainable-ai
explainable-ml
xai
interpretable-machine-learning
explainability
multilabel-model
xai-library
-
Updated
Mar 31, 2020 - Jupyter Notebook
B.Tech Project
-
Updated
May 9, 2020 - Python
Improve this page
Add a description, image, and links to the interpretable-ai topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the interpretable-ai topic, visit your repo's landing page and select "manage topics."
Yes