ATP

Deep learning adaptation

An implementation of adaptive test-time personalization for federated learning in deep neural networks.

[NeurIPS 2023] Adaptive Test-Time Personalization for Federated Learning. Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He.

GitHub

16 stars
2 watching
0 forks
Language: Python
last commit: 11 months ago
federated-learningpersonalized-federated-learningtest-time-adaptation

Related projects:

Repository Description Stars
wenkehuang/rethinkfl Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains 92
zhenqincn/fedapen An implementation of cross-silo federated learning with adaptability to statistical heterogeneity 12
atuannguyen/fedsr An implementation of a domain generalization method for federated learning using Python and PyTorch 26
xiyuanyang45/dynamicpfl A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness 55
wasidennis/adaptsegnet This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. 850
baowenxuan/fedcollab An algorithm that optimizes collaboration in federated learning by clustering clients into non-overlapping coalitions based on data quantity and pairwise distribution distances. 16
sungwon-han/fedx An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels. 68
royson/fedl2p This project enables personalized learning models by collaborating on learning the best strategy for each client 19
tsingz0/fedala An implementation of a federated learning method for personalized models on non-iid datasets. 114
omarfoq/knn-per A federated learning framework with personalized memorization using deep neural networks and k-nearest neighbors for collaborative learning of statistical models 43
mediabrain-sjtu/pfedgraph This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets. 26
easezyc/deep-transfer-learning A collection of implementations of algorithms to adapt deep learning models from one domain to another 897
pengyang7881187/fedrl Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data 54
tsingz0/fedcp A framework that separates feature information from data in federated learning to enable personalized models. 25
google-deepmind/meltingpot Assesses generalization of multi-agent reinforcement learning algorithms to novel social situations 626