edenruffell

edenruffell's Stars

• warisgill/TraceFL

  TraceFL is a novel mechanism for Federated Learning that achieves interpretability by tracking neuron provenance. It identifies clients responsible for global model predictions, achieving 99% accuracy across diverse datasets (e.g., medical imaging) and neural networks (e.g., GPT).

  Language:Python6

• xujialiu/my_lightning_model

  Language:Jupyter Notebook1

• APPFL/APPFL

  Advanced Privacy-Preserving Federated Learning framework

  Language:Python7416

• lishenghui/awesome-fm-fl

  ✨✨A curated list of latest advances on Foundation Models with Federated Learning

  Language:Python362

• QTIM-Lab/federatedLearning_glaucoma_segmentation

  Federated Learning Optic Disc and Cup Segmentation Model for Glaucoma Monitoring in Color Fundus Photographs(CFPs)

  Language:Python1

• QTIM-Lab/FL_ViT_pretraining

  Language:Python2

• albarqouni/Federated-Learning-In-Healthcare

  A list of papers on Federated Deep Learning in Healthcare, in particular, algorithms Deep Learning with Medical Imaging.

  317

• monk1337/Aweome-Heathcare-Federated-Learning

  A curated list of Federated Learning papers/articles and recent advancements.

  8017

• QTIM-Lab/dinov2_imagenet1k_example

  To get DinoV2 running on a non-slurm environment on ImageNet 1K

  Language:Python42

• hannah2gah/diabetic-retinopathy-debrecen-dataset-machine-learning

  First Machine Learning project about classification of eye abnormality

  Language:Jupyter Notebook41

• EleutherAI/lm-evaluation-harness

  A framework for few-shot evaluation of language models.

  Language:Python6.6k1.7k

• apple/pfl-research

  Simulation framework for accelerating research in Private Federated Learning

  Language:Jupyter Notebook28627

• allgebrist/Causal-Deconvolution-of-Networks

  Causal Deconvolution of Networks by Algorithmic Generative Models

  Language:R2910

• huggingface/peft

  🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

  Language:Python16k1.6k

• pytorch/captum

  Model interpretability and understanding for PyTorch

  Language:Python4.8k489

• TsingZ0/PFLlib

  37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.

  Language:Python1.4k290

• facebookresearch/mae

  PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

  Language:Python7.2k1.2k

• openmedlab/RETFound_MAE

  RETFound - A foundation model for retinal image

  Language:Jupyter Notebook665

• rmaphoh/RETFound_MAE

  RETFound - A foundation model for retinal image

  Language:Jupyter Notebook34376

• adap/flower

  Flower: A Friendly Federated AI Framework

  Language:Python4.9k847

• YipengHu/MPHY0030

  UCL Module: Programming Foundations for Medical Image Analysis

  Language:Jupyter Notebook114

• larsmaaloee/auxiliary-deep-generative-models

  Deep generative models for semi-supervised learning.

  Language:Python10928

• saemundsson/semisupervised_vae

  Replication of Semi-Supervised Learning with Deep Generative Models

  Language:Python9837

• musyoku/variational-autoencoder

  Chainer implementation of Variational AutoEncoder (VAE) M1 / M2 / M1+M2

  Language:Python235

• dpkingma/nips14-ssl

  Code for reproducing results of NIPS 2014 paper "Semi-Supervised Learning with Deep Generative Models"

  Language:Python505149

• wohlert/semi-supervised-pytorch

  Implementations of various VAE-based semi-supervised and generative models in PyTorch

  Language:Python704123

• bjlkeng/sandbox

  Play time!

  Language:Jupyter Notebook19571

• guilherme-pombo/vae_lesion_deficit

  Lesion-deficit mapping/inference with VAEs

  Language:Jupyter Notebook7

• guilherme-pombo/CounterSynth

  Code for Equitable modelling of brain imaging by counterfactual augmentation with 3D deep generative models

  Language:Python71

• marrlab/ClassificationALL

  Accurate classification of blood cells in a small acute lymphoblastic leukemia dataset using convolutional neural networks

  Language:Python5