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visitworld123 / FedFed[NeurIPS 2023] "FedFed: Feature Distillation against Data Heterogeneity in Federated Learning"
PMBio / ScLVMscLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation.
UniprJRC / FSDAFlexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.
JEFworks-Lab / MERINGUEcharacterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities
raphael-group / THetATumor Heterogeneity Analysis (THetA) and THetA2 are algorithms that estimate the tumor purity and clonal/subclonal copy number aberrations directly from high-throughput DNA sequencing data. This repository includes the updated algorithm, called THetA2.
liecn / PyramidFL[ACM MobiCom 2022] "PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.
mtuann / Federated Learning Updated PapersPapers related to Federated Learning in all top venues
TsingZ0 / FedTGPAAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning
mmendiet / FedAlignOfficial repository for Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning [CVPR 2022 Oral, Best Paper Finalist]
Yutong-Dai / FedNHCode release for Tackling Data Heterogeneity in Federated Learning with Class Prototypes appeared on AAAI2023.
MMorafah / Sub FedAvgPersonalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity
wizard1203 / VHLICML2022: Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
vladislav-morozov / Econometrics HeterogeneityCausal Inference in Observational Data with Unobserved Heterogeneity (Lecture Notes. Masters/PhD-level)
ZFancy / SFAT[ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"
MMorafah / FL SC NIIDRethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks
ai-spatial / STARCode for learning with data heterogeneity (ICDM'21 Best Paper Award)
Urban-Analytics / Data Driven Car FollowingDevelopment of parametric, deep learning, and reinforcement learning agent-based model of car-following behaviour. The models aim to be data-driven, and take into account the heterogeneity of drivers' behaviour and vehicle types. Potential future applications include investigation of a mixed traffic of human-driven vehicles and autonomous vehicles.
UCSC-VLAA / FedConv[TMLR'24] This repository includes the official implementation our paper "FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning"
zhengtaoxiao / Single Cell Metabolic LandscapePipeline for characterizing metebolic heterogeneity from single-cell RNA-seq data
Kthyeon / Ssfod[Official] NeurIPS 2023, "Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection"
