#
explainable-artificial-intelligence
Here are 40 public repositories matching this topic...
A generalized gradient-based CNN visualization technique
deep-learning
tensorflow
grad-cam
cnn
convolutional-neural-networks
explainable-artificial-intelligence
cnn-visualization-technique
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Updated
Apr 17, 2019 - Python
A Python package that implements a novel text classifier (SS3) with visualizations tools for Explainable Artificial Intelligence (XAI)
nlp
machine-learning
natural-language-processing
text-mining
data-mining
text-classification
machine-learning-algorithms
artificial-intelligence
document-classification
sentence-classification
interpretability
multilabel-classification
explainable-artificial-intelligence
interpretable-ml
xai
interpretable-machine-learning
document-categorization
early-classification
text-labeling
ss3-classifier
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Updated
May 27, 2020 - Python
hbaniecki
commented
Feb 17, 2020
modelStudio FAQ & Troubleshooting
- Error occurred during the
modelStudio()computation fooplot doesn't show up on the dashboard
- Read the console output of
DALEX::explain(). There could be a warning message pointing to the
Visualizing how deep networks make decisions
visualization
python
computer-vision
deep-learning
backpropagation
excitation
contrastive
explainable-artificial-intelligence
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Updated
Jul 12, 2019 - Jupyter Notebook
Model verification, validation, and error analysis
machine-learning
classification
regression-models
model-validation
error-analysis
residuals
explainable-artificial-intelligence
xai
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Updated
May 28, 2020 - R
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
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Updated
Feb 5, 2020 - Python
Learning Finite State Representations of Recurrent Policy Networks
deep-reinforcement-learning
pytorch
recurrent-neural-networks
finite-state-machine
tomita
atari
quantization
bottleneck
interpretability
moore-machine
explainable-artificial-intelligence
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Updated
Oct 29, 2019 - Python
All about explainable AI, algorithmic fairness and more
interpretability
explainable-artificial-intelligence
interpretable-deep-learning
interpretable-ai
explainable-ai
explainable-ml
interpretable-machine-learning
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Updated
Jun 12, 2020
A CUDA implementation of the Tsetlin Machine based on bitwise operators
cuda
pattern-recognition
gpu-computing
bitwise-operators
explainable-artificial-intelligence
tsetlin-machine
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Updated
Aug 19, 2019 - Cuda
This project provides GOLang implementation of Neuro-Evolution of Augmented Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima
golang
neat
neuroevolution
reinforcement-learning-algorithms
artificial-neural-networks
unsupervised-learning
unsupervised-learning-algorithms
augmenting-topologies
unsupervised-machine-learning
novelty-search
explainable-artificial-intelligence
explainable-ai
modular-ai
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Updated
Jul 30, 2019 - Go
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
machine-learning
human-in-the-loop
interpretability
explainable-artificial-intelligence
researchers
interactive-machine-learning
deep-learning-visualization
human-in-the-loop-machine-learning
explainable-ml
xai
interpretable
interpretable-machine-learning
iml
model-interpretability
explainable
interpretable-models
explainable-models
interpretable-learning
explaining-ai
explanation-methods
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Updated
Jun 7, 2020 - R
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments
diversity
news
recommendation-system
simulations
recommendation-engine
simulation-toolkit
explainable-artificial-intelligence
explainable-ai
fairness-ai
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Updated
Nov 6, 2018 - Python
Automated Transparent Genetic Feature Engineering
python
machine-learning
genetic-algorithm
feature-engineering
explainable-artificial-intelligence
explainable-ai
explainable-ml
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Updated
Nov 28, 2019
Code and data from the paper "Targeted Nonlinear Adversarial Perturbations in Images and Videos".
adversarial-networks
adversarial-learning
adversarial-examples
explainable-artificial-intelligence
perturbation-analysis
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Updated
Sep 8, 2018 - Jupyter Notebook
Explanations in Multi-Model Planning
planning
human-robot-interaction
automated-reasoning
planning-domain-definition-language
planning-algorithms
explainable-artificial-intelligence
explainable-ai
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Updated
Oct 30, 2019 - Python
Repository for Kubach et al. bioRxiv/2019/804682 (2019)
machine-learning
deep-learning
grad-cam
convolutional-neural-network
medical-images
epilepsy
pathology
explainable-artificial-intelligence
guided-grad-cam
histopathology
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Updated
Jan 28, 2020 - Python
DEPRECATED A server to provide Anchor-Explanations for machine learning models
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Updated
Jan 30, 2020 - Java
Interactive XAI dashboard
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Updated
Jun 3, 2020 - Vue
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 any Black-Box Machine Learning Model with explainX.ai : Fast, Scalable & State-of-the-art Explainable AI Platform.
python
machine-learning
ai
jupyter-notebook
artificial-intelligence
trust
transparency
blackbox
bias
interpretability
explainable-artificial-intelligence
interpretable-deep-learning
interpretable-ai
explainable-ai
explainable-ml
xai
interpretable-machine-learning
explainability
explainx
remove-biases
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Updated
Jun 18, 2020 - Python
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Updated
Oct 10, 2019
A tool for security assessment of multi-service IoT application deployment in the Fog.
iot
security
probabilistic-programming
trust
logic-programming
fog-computing
problog
declarative-programming
explainable-artificial-intelligence
security-assessments
cloud-edge
explainable-ai
fog-applications
explainable-security
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Updated
Apr 8, 2020 - Prolog
A scalable, explainable Java Naive Bayes Classifier that works either in memory or on persistent fast key-value store (MapDB, RocksDB or LevelDB)
rocksdb
leveldb
naive-bayes-classifier
naive-bayes-algorithm
mapdb
naive-bayes-classification
explainable-artificial-intelligence
explainable-ai
naivebayesclassifier
explain-classifiers
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Updated
Jan 20, 2020 - Java
Sensitivity Analysis for Understanding Complex Computational Models
machine-learning
r
statistics
simulation
artificial-intelligence
calibration
sensitivity-analysis
simulation-toolkit
simulation-modeling
explainable-artificial-intelligence
explainable-ai
explainable-ml
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Updated
Apr 18, 2016 - R
The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.
golang
reinforcement-learning
neat
neuroevolution
unsupervised-learning-algorithms
hyperneat
unsupervised-machine-learning
artifical-neural-network
explainable-artificial-intelligence
modular-ai
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Updated
Apr 12, 2019 - Go
This tool can be used to find the most influential words on a document. We define most influential as the words that influence a trained classifier the most to give it a particular classification.
python
machine-learning
classification
convolutional-neural-networks
gradients
nlp-machine-learning
keras-tensorflow
vocabulary-analysis
wikileaks
adversarial-machine-learning
imdb-sentiment-analysis
explainable-artificial-intelligence
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Updated
May 9, 2018 - Python
R implementation of Contextual Importance and Utility for Explainable AI
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Updated
May 12, 2020 - R
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General:
DALEX_docsR specific:
titanicandapartmentsexplain()predict_parts()predict_profile()