Alternatives and similar repositories for federated-model-aggregation:

Users that are interested in federated-model-aggregation are comparing it to the libraries listed below

• facebookresearch / synlm
  Code for paper: "Privately generating tabular data using language models".
  ☆15Updated last year
• awslabs / privacy-preserving-xgboost-inference
  Privacy-preserving XGBoost Inference
  ☆48Updated last year
• leriomaggio / ppml-tutorial
  Privacy-Preserving Machine Learning (PPML) Tutorial
  ☆37Updated 8 months ago
• DataResponsibly / MirrorDataGenerator
  MirrorDataGenerator is a python tool that generates synthetic data based on user-specified causal relations among features in the data. I…
  ☆21Updated 2 years ago
• opendp / smartnoise-core-python
  Python language bindings for smartnoise-core.
  ☆75Updated last year
• microsoft / msrflute
  Federated Learning Utilities and Tools for Experimentation
  ☆187Updated last year
• sarus-tech / dp-xgboost
  ☆23Updated last year
• EthicalML / sml-security
  MLOps Cookiecutter Template: A Base Project Structure for Secure Production ML Engineering
  ☆40Updated 3 months ago
• IBM / ai-privacy-toolkit
  A toolkit for tools and techniques related to the privacy and compliance of AI models.
  ☆99Updated 7 months ago
• opendp / smartnoise-samples
  Code samples and documentation for SmartNoise differential privacy tools
  ☆132Updated 2 years ago
• gretelai / public_research
  Where Gretel published notebooks and code for blog posts
  ☆19Updated last year
• gretelai / awesome-synthetic-data
  📖 A curated list of resources dedicated to synthetic data
  ☆125Updated 2 years ago
• aws-samples / federated-learning-greengrass-ecs
  ☆17Updated 9 months ago
• ForestFlow / ForestFlow
  ForestFlow is a policy-driven Machine Learning Model Server. It is an LF AI Foundation incubation project.
  ☆72Updated last year
• capeprivacy / cape-dataframes
  Privacy transformations on Spark and Pandas dataframes backed by a simple policy language.
  ☆174Updated last year
• inaccel / heflow
  Open source platform for the privacy-preserving machine learning lifecycle
  ☆17Updated last year
• leriomaggio / privacy-preserving-data-science
  Course Material for the Tutorial on Privacy Enhancing Technologies and PPML
  ☆12Updated 3 years ago
• DeltaML / federated-learning-poc
  Proof of Concept of a Federated Learning framework that maintains the privacy of the participants involved.
  ☆14Updated 2 years ago
• DreamingRaven / python-fhez
  Official mirror of Python-FHEz; Python Fully Homomorphic Encryption (FHE) Library for Encrypted Deep Learning as a Service (EDLaaS).
  ☆29Updated 2 years ago
• ourownstory / federated_kmeans
  Federated k-means clustering algorithm implementation and proof of concept.
  ☆28Updated 3 years ago
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆27Updated 6 months ago
• ray-project / mlflow-ray-serve
  MLFlow Deployment Plugin for Ray Serve
  ☆43Updated 2 years ago
• OpenMined / PipelineDP
  PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such a…
  ☆274Updated 3 weeks ago
• facebookarchive / fronni
  machine learning model performance metrics & charts with confidence intervals, optimized with numba to be fast
  ☆16Updated 3 years ago
• data-dev / DataTracer
  Data Lineage Tracing Library
  ☆22Updated 3 years ago