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explainability

Here are 46 public repositories matching this topic...

slundberg / shap

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A game theoretic approach to explain the output of any machine learning model.

machine-learning deep-learning gradient-boosting interpretability shapley shap explainability

Updated Aug 7, 2020
Jupyter Notebook

EthicalML / awesome-production-machine-learning

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A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

machine-learning data-mining privacy deep-learning interpretability privacy-preserving production-machine-learning mlops privacy-preserving-machine-learning explainability responsible-ai responsible-ml machine-learning-operations ml-ops ml-operations privacy-preserving-ml large-scale-ml production-ml large-scale-machine-learning

Updated Aug 8, 2020

interpretml / interpret

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Fit interpretable models. Explain blackbox machine learning.

machine-learning ai scikit-learn artificial-intelligence transparency blackbox bias gradient-boosting interpretability interpretable-ai interpretable-ml explainable-ai explainable-ml xai interpretable-machine-learning iml machine-learning-interpretability explainability interpretml

Updated Aug 8, 2020
C++

EthicalML / xai

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XAI - An eXplainability toolbox for machine learning

machine-learning ai evaluation ml artificial-intelligence upsampling bias interpretability feature-importance explainable-ai explainable-ml xai imbalance downsampling explainability bias-evaluation machine-learning-explainability xai-library

Updated Oct 5, 2019
Python

MisaOgura / flashtorch

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Visualization toolkit for neural networks in PyTorch! Demo -->

visualization machine-learning deep-learning cnn pytorch neural-networks interpretability explainability

Updated May 29, 2020
Python

alvinwan / neural-backed-decision-trees

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Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

pytorch neural-networks imagenet image-classification pretrained-models decision-trees cifar10 interpretability pretrained-weights cifar100 tiny-imagenet explainability neural-backed-decision-trees

Updated Jun 17, 2020
Python

modelStudio

ModelOriented / modelStudio

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📍 Interactive Studio for Explanatory Model Analysis

machine-learning predictive-modeling interactive-visualizations interpretability explainable-artificial-intelligence explainable-ai explainable-ml xai model-visualization interpretable-machine-learning iml explainability explanatory-model-analysis explainable-machine-learning

Updated Aug 6, 2020
R

hierarchical-dnn-interpretations

csinva / hierarchical-dnn-interpretations

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Using / reproducing ACD (ICLR 2019) from the paper "Hierarchical interpretations for neural network predictions"

python data-science machine-learning statistics deep-neural-networks ai deep-learning neural-network jupyter-notebook ml pytorch artificial-intelligence convolutional-neural-networks acd interpretation interpretability feature-importance explainable-ai iclr2019 explainability

Updated Jul 23, 2020
Jupyter Notebook

d909b / cxplain

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Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.

machine-learning deep-learning interpretability explainable-ai explainable-ml explainability

Updated Jan 27, 2020
Python

graph-network-explainability

baldassarreFe / graph-network-explainability

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Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)

bioinformatics artificial-intelligence graph-networks explainability

Updated Nov 12, 2019
Jupyter Notebook

haofanwang / Score-CAM

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[CVPR 2020 Workshop] Official implementation of Score-CAM in Pytorch

heatmap pytorch cam saliency class-activation-maps cnn-visualization-technique gradient-free cnn-visualization visual-explanations explainability score-cam scorecam

Updated Jun 20, 2020
Python

deep-explanation-penalization

laura-rieger / deep-explanation-penalization

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Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

python data-science machine-learning ai deep-learning neural-network jupyter-notebook ml pytorch artificial-intelligence convolutional-neural-network fairness interpretability cdep feature-importance recurrent-neural-network interpretable-deep-learning explainable-ai explainability fairness-ml

Updated Jul 23, 2020
Jupyter Notebook

SAP / contextual-ai

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Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference - thereby addressing the trust gap between such ML systems and their users. It does not refer to a specific algorithm or ML method — instead, it takes a human-centric view and approach to AI.

machine-learning report-generator explainability

Updated Jul 28, 2020
Jupyter Notebook

sebastian-hofstaetter / transformer-kernel-ranking

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TK & TKL - Efficient Transformer-based neural re-ranking models

efficiency transformer explainability neural-ir

Updated Jul 28, 2020
Python

WHUIR / CARP

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The implementation of “A Capsule Network for Recommendation and Explaining What You Like and Dislike”, Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu, https://dl.acm.org/citation.cfm?doid=3331184.3331216

recommendation explainability caspule-network

Updated Feb 1, 2020
Python

fat-forensics / fat-forensics

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Modular Python Toolbox for Fairness, Accountability and Transparency Forensics

machine-learning transparency fairness accountability interpretability interpretable-ai explainable-ai explainability

Updated Aug 8, 2020
Python

awslabs / sagemaker-explaining-credit-decisions

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Amazon SageMaker Solution for explaining credit decisions.

machinelearning financial-analysis credit-scoring explainable-ai explainable-ml sagemaker loan-prediction-analysis shapley explainability aws-sagemaker

Updated Jun 8, 2020
Python

iancovert / sage

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For calculating global feature importance using Shapley values.

machine-learning interpretability shapley explainability

Updated Jun 8, 2020
Python

ArenaR

ModelOriented / ArenaR

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Data generator for Arena - interactive XAI dashboard

ema interpretability xai iml explainability explanatory-model-analysis axplainable-artificial-intelligence interactive-xai

Updated Jul 29, 2020
R

AgaMiko / GEBI

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GEBI: Global Explanations for Bias Identification. Open source code for discovering bias in data with skin lesion dataset

deep-learning explainable-ai attention-maps explainability global-explanation

Updated May 6, 2020
Jupyter Notebook

xyli1905 / DeepInfoFlow

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machine-learning dynamics mutual-information explainability full-connected-neural-network

Updated Jul 15, 2019
Python

viadee / javaAnchorAdapters

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Getting the Anchors Explainer to work in Different Settings

java machine-learning ai anchors explainability

Updated Jul 1, 2020
Java

dmitrykazhdan / MARLeME

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General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems

library reinforcement-learning rl model-extraction lime plug-and-play interpretability reinforcement-learning-agent open-ai abstract-argumentation explanations multi-agent-reinforcement-learning open-ai-gym knowledge-extraction explainability marl model-extractor extracting-interpretable-models

Updated May 10, 2020
C++

12wang3 / mllp

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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

koriavinash1 / BioExp

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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 Jul 9, 2020
Python

pnxenopoulos / cav-keras

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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

archiki / ASR-Accent-Analysis

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Analysis and investigating the confounding effect of accents in E-2-E Automatic Speech Recognition models.

analysis pytorch automatic-speech-recognition probes mutual-information accents interpretability phones end-to-end-learning representation-similarity deepspeech explainability gradient-analysis accent-adaptation

Updated Jun 27, 2020
Jupyter Notebook

transformation-importance

csinva / transformation-importance

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Using / reproducing TRIM from the paper "Transformation Importance with Applications to Cosmology"

data-science machine-learning deep-neural-networks ai deep-learning neural-network attribution ml pytorch artificial-intelligence transform feature-engineering transformation frequency-domain interpretation interpretability wavelet-analysis feature-importance explainable-ai explainability

Updated Jul 23, 2020
Jupyter Notebook

jettify / ibreakdown

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ibreakdown is model agnostic predictions explainer with interactions support, library can show contribution of each feature of your prediction value

explainable-ai xai explainability xai-library

Updated Aug 5, 2020
Jupyter Notebook

teller

thierrymoudiki / teller

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Model-agnostic Machine Learning explainability

machine-learning statistical-learning springer james xai explainability xai-library gareth

Updated Jun 5, 2020
Jupyter Notebook

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