Topic: interpretability Goto Github

👇 Here are 640 public repositories matching this topic...

alvinwan / neural-backed-decision-trees
interpretability,Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
User: alvinwan
Home Page: https://nbdt.aaalv.in
decision-trees neural-networks image-classification explainability tiny-imagenet cifar10 cifar100 interpretability imagenet neural-backed-decision-trees

bcg-x-official / facet
interpretability,Human-explainable AI.
Organization: bcg-x-official
Home Page: https://bcg-x-official.github.io/facet
data-analytics data-science explainable-ai hyperparameter-tuning interpretability machine-learning model-selection python shap-vector-decomposition simulation statistics

cdpierse / transformers-interpret
interpretability,Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
User: cdpierse
nlp machine-learning natural-language-processing explainable-ai transformers model-explainability transformers-model captum deep-learning neural-network

chaoyanghe / awesome-federated-learning
interpretability,FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
User: chaoyanghe
federated-learning machine-learning distributed-optimization non-iid vertical-federated-learning decentralized-federated-learning hierarchical-federated-learning neural-architecture-search transfer-learning continual-learning

csinva / imodels
interpretability,Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
User: csinva
Home Page: https://csinva.io/imodels
interpretability machine-learning data-science artificial-intelligence ml ai statistics scikit-learn python optimal-classification-tree

datamllab / awesome-fairness-in-ai
interpretability,A curated list of awesome Fairness in AI resources
Organization: datamllab
fairness machine-learning deep-learning gender-bias xai interpretability bias ai

deel-ai / xplique
interpretability,👋 Xplique is a Neural Networks Explainability Toolbox
Organization: deel-ai
Home Page: https://deel-ai.github.io/xplique
explainable-ai explainable-ml interpretability xai

ethicalml / awesome-production-machine-learning
interpretability,A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Organization: ethicalml
Home Page: https://ethicalml.github.io/awesome-production-machine-learning
machine-learning mlops interpretability explainability responsible-ai deep-learning machine-learning-operations ml-ops ml-operations privacy-preserving

ethicalml / xai
interpretability,XAI - An eXplainability toolbox for machine learning
Organization: ethicalml
Home Page: https://ethical.institute/principles.html#commitment-3
explainability xai ml ai bias artificial-intelligence bias-evaluation explainable-ai explainable-ml machine-learning

explainx / explainx
interpretability,Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
Organization: explainx
explainable-ai explainable-artificial-intelligence machine-learning interpretability blackbox xai explainx interpretable-ai transparency bias

frgfm / torch-cam
interpretability,Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
User: frgfm
Home Page: https://frgfm.github.io/torch-cam/
pytorch python deep-learning cnn activation-maps gradcam-plus-plus gradcam saliency-map interpretability interpretable-deep-learning

google-deepmind / penzai
interpretability,A JAX research toolkit for building, editing, and visualizing neural networks.
Organization: google-deepmind
Home Page: https://penzai.readthedocs.io/
fine-tuning interpretability jax neural-networks visualization

google / yggdrasil-decision-forests
interpretability,A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Organization: google
Home Page: https://ydf.readthedocs.io/
cpp cli tensorflow machine-learning ml decision-trees decision-forest random-forest gradient-boosting cart interpretability distributed-computing go javascript pypi python

h2oai / mli-resources
interpretability,H2O.ai Machine Learning Interpretability Resources
Organization: h2oai
machine-learning python jupyter-notebooks interpretability data-science data-mining h2o mli xai fatml

hbaniecki / adversarial-explainable-ai
interpretability,💡 Adversarial attacks on explanations and how to defend them
User: hbaniecki
Home Page: https://doi.org/10.1016/j.inffus.2024.102303
interpretable-machine-learning adversarial-machine-learning iml adversarial-attacks interpretability xai explainable-ai adversarial-examples explainability attacks

hila-chefer / transformer-mm-explainability
interpretability,[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
User: hila-chefer
transformers transformer vqa detr visualization explainability explainable-ai interpretability lxmert visualbert

inseq-team / inseq
interpretability,Interpretability for sequence generation models 🐛 🔍
Organization: inseq-team
Home Page: https://inseq.org
interpretability deep-learning transformers explainable-ai captum huggingface attribution-methods natural-language-processing generative-ai language-generation

interpretml / interpret
interpretability,Fit interpretable models. Explain blackbox machine learning.
Organization: interpretml
Home Page: https://interpret.ml/docs
machine-learning interpretability gradient-boosting blackbox scikit-learn xai interpretml interpretable-machine-learning interpretable-ai transparency

jacobgil / pytorch-grad-cam
interpretability,Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
User: jacobgil
Home Page: https://jacobgil.github.io/pytorch-gradcam-book
deep-learning pytorch grad-cam visualizations interpretability interpretable-ai interpretable-deep-learning score-cam class-activation-maps vision-transformers

jphall663 / awesome-machine-learning-interpretability
interpretability,A curated list of awesome responsible machine learning resources.
User: jphall663
fairness xai interpretability transparency machine-learning data-science python r awesome awesome-list

jphall663 / interpretable_machine_learning_with_python
interpretability,Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
User: jphall663
machine-learning python fatml xai gradient-boosting-machine decision-tree data-science fairness interpretable-machine-learning interpretability

kmeng01 / rome
interpretability,Locating and editing factual associations in GPT (NeurIPS 2022)
User: kmeng01
Home Page: https://rome.baulab.info
transformers gpt interpretability pytorch

kundajelab / deeplift
interpretability,Public facing deeplift repo
Organization: kundajelab
deeplift sensitivity-analysis integrated-gradients guided-backpropagation saliency-map interpretable-deep-learning interpretability

linkedin / fasttreeshap
interpretability,Fast SHAP value computation for interpreting tree-based models
Organization: linkedin
explainable-ai interpretability lightgbm machine-learning random-forest shap xgboost

maif / shapash
interpretability,🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Organization: maif
Home Page: https://maif.github.io/shapash/
python machine-learning explainability explainable-ml transparency ethical-artificial-intelligence shap lime interpretability

microsoft / responsible-ai-toolbox
interpretability,Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
Organization: microsoft
Home Page: https://responsibleaitoolbox.ai/
ui responsible-ai data-science fairness fairness-ml fairness-ai explainable-ai explainable-ml explainability machinelearning

misaogura / flashtorch
interpretability,Visualization toolkit for neural networks in PyTorch! Demo -->
User: misaogura
Home Page: https://youtu.be/18Iw4qYqfPo
pytorch neural-networks cnn interpretability machine-learning deep-learning visualization explainability

modeloriented / dalex
interpretability,moDel Agnostic Language for Exploration and eXplanation
Organization: modeloriented
Home Page: https://dalex.drwhy.ai
machine-learning interpretability data-science xai iml model-visualization dalex explanations explainable-ai explainable-artificial-intelligence

modeloriented / modelstudio
interpretability,📍 Interactive Studio for Explanatory Model Analysis
Organization: modeloriented
Home Page: https://doi.org/10.1007/s10618-023-00924-w
xai iml interpretability interpretable-machine-learning explanatory-model-analysis explainable-ai explainable-machine-learning model-visualization learning machine

ndif-team / nnsight
interpretability,The nnsight package enables interpreting and manipulating the internals of deep learned models.
Organization: ndif-team
Home Page: https://nnsight.net/
interpretability machine-learning neural-networks python pytorch

onetaken / awesome_deep_learning_interpretability
interpretability,深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
User: onetaken
interpretability deep-learning computer-vision awesome awesome-list papers pytorch tensorflow keras torch

pbiecek / xai_resources
interpretability,Interesting resources related to XAI (Explainable Artificial Intelligence)
User: pbiecek
xai interpretability interpretable-machine-learning

pratyushasharma / laser
interpretability,The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
User: pratyushasharma
Home Page: https://pratyushasharma.github.io/laser/
gpt-j interpretability laser llama2 llm llms model-compression transformers

pytorch / captum
interpretability,Model interpretability and understanding for PyTorch
Organization: pytorch
Home Page: https://captum.ai
interpretability interpretable-ai interpretable-ml feature-importance feature-attribution

ramprs / grad-cam
interpretability,[ICCV 2017] Torch code for Grad-CAM
User: ramprs
Home Page: https://arxiv.org/abs/1610.02391
iccv17 grad-cam interpretability convolutional-neural-networks deep-learning heatmap visual-explanation

scalaconsultants / aspect-based-sentiment-analysis
interpretability,💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
Organization: scalaconsultants
aspect-based-sentiment-analysis tensorflow sentiment-analysis machine-learning interpretability distill transformers transformer-models bert-embeddings deep-learning

seldonio / alibi
interpretability,Algorithms for explaining machine learning models
Organization: seldonio
Home Page: https://docs.seldon.io/projects/alibi/en/stable/
machine-learning explanations interpretability counterfactual xai

sergioburdisso / pyss3
interpretability,A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
User: sergioburdisso
Home Page: https://pyss3.readthedocs.io
xai text-classification machine-learning machine-learning-algorithms artificial-intelligence explainable-artificial-intelligence data-mining early-classification ss3-classifier nlp

shap / shap
interpretability,A game theoretic approach to explain the output of any machine learning model.
Organization: shap
Home Page: https://shap.readthedocs.io
interpretability machine-learning deep-learning gradient-boosting shap shapley explainability

shubhomoydas / ad_examples
interpretability,A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
User: shubhomoydas
ensemble-learning active-learning anomaly-detection rnn lstm explaination interpretability time-series timeseries trees

sicara / tf-explain
interpretability,Interpretability Methods for tf.keras models with Tensorflow 2.x
Organization: sicara
Home Page: https://tf-explain.readthedocs.io
interpretability deep-learning tensorflow tf2 keras visualization machine-learning

stanfordnlp / pyreft
interpretability,ReFT: Representation Finetuning for Language Models
Organization: stanfordnlp
Home Page: https://arxiv.org/abs/2404.03592
interpretability reft representation-finetuning

stanfordnlp / pyvene
interpretability,Stanford NLP Python Library for Understanding and Improving PyTorch Models via Interventions
Organization: stanfordnlp
Home Page: http://pyvene.ai
interpretability mechanistic-interpretability intervention activation-intervention activation-patching

stellargraph / stellargraph
interpretability,StellarGraph - Machine Learning on Graphs
Organization: stellargraph
Home Page: https://stellargraph.readthedocs.io/
graphs machine-learning machine-learning-algorithms graph-convolutional-networks networkx geometric-deep-learning saliency-map interpretability heterogeneous-networks graph-neural-networks graph-analysis graph-machine-learning gcn link-prediction stellargraph-library graph-data python deep-learning data-science

tensorflow / decision-forests
interpretability,A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Organization: tensorflow
python machine-learning random-forest tensorflow ml decision-trees gradient-boosting interpretability decision-forest keras

tensorflow / lucid
interpretability,A collection of infrastructure and tools for research in neural network interpretability.
Organization: tensorflow
tensorflow interpretability visualization machine-learning colab jupyter-notebook

tensorflow / tcav
interpretability,Code for the TCAV ML interpretability project
Organization: tensorflow
interpretability machine-learning tcav

understandable-machine-intelligence-lab / quantus
interpretability,Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
Organization: understandable-machine-intelligence-lab
Home Page: https://quantus.readthedocs.io/
machine-learning explainable-ai quantification-evaluation-methods deep-learning pytorch tensorflow interpretability xai reproducibility

wangyongjie-ntu / awesome-explainable-ai
interpretability,A collection of research materials on explainable AI/ML
User: wangyongjie-ntu
interpretable-ai explainable-ai interpretability explanation-system xai xml counterfactual-explanations recourse

xmed-lab / clip_surgery
interpretability,CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks
Organization: xmed-lab
clip sam explainability multimodal multilabel segmentation open-vocabulary segment-anything interpretability vision-transformer