FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients

16 November 2023

Papers citing "FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients"

4 / 4 papers shown

Title
Enhancing Sample Efficiency and Exploration in Reinforcement Learning through the Integration of Diffusion Models and Proximal Policy Optimization Gao Tianci Dmitriev D. Dmitry Konstantin A. Neusypin Yang Bo Rao Shengren OffRL 13 1 0 02 Sep 2024
Label-Efficient Semantic Segmentation with Diffusion Models Dmitry Baranchuk Ivan Rubachev A. Voynov Valentin Khrulkov Artem Babenko DiffM VLM 187 388 0 06 Dec 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 82 712 0 03 Feb 2021
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer Jian Liang Dapeng Hu Yunbo Wang R. He Jiashi Feng 128 249 0 14 Dec 2020