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.
16 stars
2 watching
0 forks
Language: Python
last commit: about 1 year 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 | 93 |
 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 | 57 |
 wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 851 |
| 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. | 69 |
 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. | 116 |
 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 | 898 |
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 56 |
| 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 | 637 |