julianspaeth

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https://read.cv/spaethju

Julian Späth's starred repositories

federated

A collection of Google research projects related to Federated Learning and Federated Analytics.

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python-paillier

A library for Partially Homomorphic Encryption in Python

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TenSEAL

A library for doing homomorphic encryption operations on tensors

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core

:house_with_garden: Open source home automation that puts local control and privacy first.

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torchmetrics

Torchmetrics - Machine learning metrics for distributed, scalable PyTorch applications.

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SEAL

Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.

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PySyft

Perform data science on data that remains in someone else's server

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PyVertical

Privacy Preserving Vertical Federated Learning

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federated-learning-lib

A library for federated learning (a distributed machine learning process) in an enterprise environment.

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pytorch-lightning

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

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xaynet

Xaynet represents an agnostic Federated Machine Learning framework to build privacy-preserving AI applications.

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secure-kmean-clustering

Practical Privacy-Preserving K-means Clustering (PETS-2020)

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flower

Flower: A Friendly Federated AI Framework

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leaf

Leaf: A Benchmark for Federated Settings

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Pyfhel

PYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/PALISADE as backends, implemented using Cython.

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scikit-survival

Survival analysis built on top of scikit-learn

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lifelines

Survival analysis in Python

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vaccine-designer-portlet

A portlet for the interactive design of individualized vaccines

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