Cola-kk

Cola-kk's Stars

• BIT-DA/CIRL

  [CVPR 2022 Oral] Code release for "Causality Inspired Representation Learning for Domain Generalization"

  Language:Python13913

• TsingZ0/FedTGP

  AAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning

  Language:Python404

• CityChan/Federated-Hyper-Knowledge-Distillation

  Language:Python153

• med-air/HeteroPFL

  [ICLR'24] Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate

  Language:Python9

• link-er/layer-wise-lmc

  Source code for the experiments on the layer-wise linear mode connectivity in deep neural networks

  Language:Jupyter Notebook5

• MediaBrain-SJTU/FedLESAM

  [ICML 2024 spotlight] This repository contains the implementation details for the paper "Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization"

  Language:Python141

• skynbe/FedRCL

  Official Implementation of FedRCL (CVPR 2024)

  Language:Python184

• haozhaowang/DaFKD2023

  Code for CVPR2023 DaFKD : Domain-aware Federated Knowledge Distillation

  Language:Python274

• TsingZ0/HtFLlib

  You only need to configure one file to support model heterogeneity. Consistent GPU memory usage for single or multiple clients.

  Language:Python1215

• TsingZ0/FedKTL

  CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

  Language:Python463

• zerocpp/fedhkd

  Language:Python91

• hongyouc/FedBE

  FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

  Language:Python389

• ZexiLee/ICCV-2023-FedETF

  The is the official implementation of ICCV 2023 paper "No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier".

  Language:Python252

• shaoxiongji/knowledge-graphs

  A collection of research on knowledge graphs

  Language:JavaScript1.7k292

• IBM/Grapher

  Code that implements efficient knowledge graph extraction from the textual descriptions

  Language:Python15634

• germanbraun/oceangraph

  OceanGraph: Knowledge Graph for Ocean Science

  3

• Olivia-account/Military-Equipment-Knowledge-Graph-Based-on-Deep-Learning-and-Neo4j

  基于深度学习与Neo4j的军事装备知识图谱网页应用构建。本项目是一个军事武器知识图谱网页应用软件原型系统。该系统由数据爬虫、数据管理、数据处理、知识问答、新闻热点、词条查询和图谱展示七个功能模块组成。系统从互联网上爬取数据，并基于百度文心ERNIE 3.0模型对数据进行实体识别和关系抽取，将数据处理为三元组形式并存储到图数据库Neo4j中。通过数据管理和数据标注，并通过对Neo4j中的三元组数据进行自动处理和分析，实现知识问答、新闻热点、词条查询和图谱展示的功能。

  Language:Jupyter Notebook11122

• RomanGao/QAonMilitaryKG

  QAonMilitaryKG，QaSystem based on military knowledge graph that stores in mongodb which is different from the previous one, 基于mongodb存储的军事领域知识图谱问答项目，包括飞行器、太空装备等8大类，100余小类，共计5800项的军事武器知识库，该项目不使用图数据库进行存储，通过jieba进行问句解析，问句实体项识别，基于查询模板完成多类问题的查询，主要是提供一种工业界的问答**demo。

  Language:Python87180

• chenwenhang/KnowledgeGraph

  Military knowledge graph

  Language:JavaScript288

• ownthink/KnowledgeGraph

  史上最大规模1.4亿知识图谱数据免费下载，知识图谱，通用知识图谱，融合了两千五百多万的实体，拥有亿级别的实体属性关系。

  Language:Python1k155

• ownthink/KnowledgeGraphData

  史上最大规模1.4亿中文知识图谱开源下载

  Language:Python5k728

• Louis-tiany/Military-KG

  领域知识图谱数据采集、数据处理以及可视化

  Language:Vue6413

• liuhuanyong/QASystemOnMedicalKG

  A tutorial and implement of disease centered Medical knowledge graph and qa system based on it。知识图谱构建，自动问答，基于kg的自动问答。以疾病为中心的一定规模医药领域知识图谱，并以该知识图谱完成自动问答与分析服务。

  Language:Python6.5k2.2k

• NeuralCollapseApplications/ImbalancedLearning

  [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?".

  Language:Python435

• ZackZikaiXiao/FedLoGe

  Language:Python131

• lapisrocks/fedselect

  [CVPR 2024] Official Repository for "FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning"

  Language:Python191

• AC-Amiya233/FedRep

  1127

• mtics/FedRAP

  The Code for "Federated Recommender with Additive Personalization"

  Language:Python301

• LipingYi/FedGH

  FedGH: Heterogeneous Federated Learning with Generalized Global Header (MM'23)

  Language:Python132

• haozzh/FedCR

  Language:Python20