yxq572872515

yxq572872515's Stars

• junanguo/VAE-On-Fashion-MNist

  Our group aims to learn about Variational Autoencoders by training a VAE model using Keras. The dataset we used was Fashion MNIST, a collection of 28x28 pixel images split into 10 classes of clothing items. We used the encoder model to output a visualization of the dataset’s latent space, and plotted similarity between images. To learn more about VAEs, we also analyzed the mathematical models behind concept, compared the method to autoencoders + PCA, and explored applications of VAE in domains other than image generation.

  Language:Python2

• jamesahou/mnist-vae-classifier

  VAE with attached classifier trained on MNIST

  Language:Python5

• dragen1860/pytorch-mnist-vae

  Pytorch Implementation of variational auto-encoder for MNIST

  Language:Python5911

• lyeoni/pytorch-mnist-VAE

  Language:Jupyter Notebook10748

• hwalsuklee/tensorflow-mnist-VAE

  Tensorflow implementation of variational auto-encoder for MNIST

  Language:Python491183

• google-research/federated

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

  Language:Python667190

• SAP-samples/machine-learning-diff-private-federated-learning

  Simulate a federated setting and run differentially private federated learning.

  Language:Python34992

• katsura-jp/fedavg.pytorch

  A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017

  Language:Python7519

• dunzeng/FeaderatedLearning-Mxnet

  graduation project

  Language:Python21

• zmzhouXJTU/CreditCard_Fraud_Detection

  利用Logistic回归实现信用卡欺诈检测

  Language:Python4313

• FederatedAI/Practicing-Federated-Learning

  Language:Python688228

• whopriyam/Benchmarking-Differential-Privacy-and-Federated-Learning-for-BERT-Models

  Language:Jupyter Notebook162

• PrivPkt/PrivPkt

  Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)

  Language:Python11419

• gitgik/differential-privacy-federated-learning

  Curated notebooks on how to train neural networks using differential privacy and federated learning.

  Language:Jupyter Notebook6616

• Yangfan-Jiang/Federated-Learning-with-Differential-Privacy

  Implementation of dp-based federated learning framework using PyTorch

  Language:Python26549

• ipc-lab/private-ml-for-health

  Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)

  Language:Python6617

• youben11/encrypted-evaluation

  Client/Server framework for encrypted machine learning using homomorphic encryption

  Language:Python406

• ammartahir24/SecureAggregation

  An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

  Language:Python8020

• CharlieDinh/pFedMe

  Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

  Language:Python28686

• eyp/federated-learning-simulation

  Simulation of a Federated Learning scenario using Tensorflow Federated

  Language:Python63

• FedML-AI/FedML

  FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

  Language:Python4.1k773

• vaikkunth/PrivacyFL

  A Simulator for Privacy Preserving Federated Learning

  Language:Python9032

• capeprivacy/tf-world-tutorial

  TensorFlow World 2019 Tutorial: Privacy-Preserving Machine Learning with TF Encrypted & PySyft

  Language:Jupyter Notebook476

• tf-encrypted/tf-encrypted

  A Framework for Encrypted Machine Learning in TensorFlow

  Language:Python1.2k211

• ITU-AI-ML-in-5G-Challenge/PS-022-1-Privacy-Preserving-Healthcare

  Dopamine: Differentially Private Secure Federated Learning on Medical Data

  Language:Python73

• ritwikkanodia/Privacy-Preserving-Machine-Learning

  Maintaining the privacy of local server data in a federated learning framework using differential privacy by TensorFlow Privacy Library.

  Language:Jupyter Notebook2

• lainisourgod/hybrid-approach-to-ppfl

  This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)

  Language:Python204

• ihooni/XOR-Mixup

  TensorFlow experiment codes of XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning (FL' ICML 2020)

  Language:Python121

• AmanPriyanshu/Federated-Learning

  Privacy preserving learning for Federated Learning.

  Language:Jupyter Notebook51

• seanpavlak/pride-backend

  Privacy Preserving Federated Learning on a Deep Neural Network

  Language:Jupyter Notebook8