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privacy-preserving-ml

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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 awesome deep-learning awesome-list interpretability privacy-preserving production-machine-learning mlops privacy-preserving-machine-learning explainability responsible-ai machine-learning-operations ml-ops ml-operations privacy-preserving-ml large-scale-ml production-ml large-scale-machine-learning
  • Updated Dec 5, 2025

yashmaurya01 / Awesome-ML-Privacy-Mitigations

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A curated collection of privacy-preserving machine learning techniques, tools, and practical evaluations. Focuses on differential privacy, federated learning, secure computation, and synthetic data generation for implementing privacy in ML workflows.

machine-learning privacy awesome-list secure-computation differential-privacy awesome-resources synthetic-data federated-learning privacy-preserving-ml ml-security privacy-preserving-ai ml-privacy privacy-preserving-techniques
  • Updated Jun 9, 2025

Fatemerjn / Federated_Deep_Generative_Model

Star 1

This repository explores federated deep generative models with PyTorch, featuring Conditional DCGAN, FedGAN v2, and custom synchronization strategies. It demonstrates client-server training with FedAvg, non-IID data splits, and GAN evaluation, providing a foundation for research in privacy-preserving generative modeling.

transformers pytorch differential-privacy edge-computing distributed-training federated-learning deep-generative-models federated-optimization privacy-preserving-ml diffusion-models secure-aggregation federated-gan non-iid-data federated-vae ml-reproducibility
  • Updated Oct 14, 2025
  • Jupyter Notebook

hakeematyab / Reliable-Explainable-Brain-Tumor-Segmentation

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A deep learning solution for brain tumor segmentation using multi-modal MRI scans, integrating U-Net models, differential privacy, adversarial training, and explainability (Grad-CAM, attention scores) for robust and trustworthy medical AI.

computer-vision grad-cam medical-imaging unet medical-image-analysis interpretable-ai explainable-ai brain-tumor-segmentation adversarial-training segmentation-models privacy-preserving-ml deep-learning-medical
  • Updated Apr 22, 2025
  • Jupyter Notebook

chirindaopensource / measuring_economic_outlook_in_news

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End-to-End Python implementation of Beck et al.'s (2025) economic sentiment analysis framework for constructing a high-frequency economic sentiment indicator using 1024-dimensional Jina embeddings and LLM-generated training data. Features L2-regularized classification and rigorous POOS econometric validation with DM-HAC tests for GDP forecasting.

python nlp sentiment-analysis reproducible-research tensorflow scikit-learn transformers weak-supervision econometrics statsmodels computational-economics synthetic-data time-series-forecasting regularized-regression financial-modeling privacy-preserving-ml llm claude-ai jina-embeddings
  • Updated Nov 8, 2025
  • Jupyter Notebook

Ankan-Das / AegisFL

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AegisFL is a cloud-native, privacy-preserving federated learning platform. It uses TensorFlow Federated, Differential Privacy, and Secure Aggregation to train models across decentralized clients, ensuring HIPAA/GDPR compliance with cost-optimized Kubernetes deployment and real-time monitoring.

python machine-learning deep-learning simulation tensorflow differential-privacy edge-computing distributed-training emnist federated-learning privacy-preserving-ml tensorflow-federated on-device-learning
  • Updated Aug 25, 2025
  • Jupyter Notebook

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