githubcode9527's Stars
anselleeyy/logistics-back
物流后端项目,采用 Springboot 2.0 + Layui 2.3
gzc426/Java-Interview
Java 面试必会 直通BAT
guanguans/favorite-link
❤️ 每天收集喜欢的开源项目。
ty4b112/pytorch_MINERVA
zjukg/FedE
[Paper][IJCKG2021] FedE: Embedding Knowledge Graphs in Federated Setting
taokz/FedR
Official codes for paper "Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation"
liuyubobobo/Play-with-Algorithm-Interview
Codes of my MOOC Course <Play with Algorithm Interviews>. Updated contents and practices are also included. 我在慕课网上的课程《玩儿转算法面试》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。
xwhan/DeepPath
code and docs for my EMNLP paper "DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning"
HKUST-KnowComp/FKGE
Code for CIKM 2021 paper: Differentially Private Federated Knowledge Graphs Embedding (https://arxiv.org/abs/2105.07615)
txsun1997/CoLAKE
COLING'2020: CoLAKE: Contextualized Language and Knowledge Embedding
ameyagodbole/Prob-CBR
YushanZhu/K3M
Code and Data for paper: Knowledge Perceived Multi-modal Pretraining in E-commerce (ACM MM2021)
xkLi-Allen/Awesome-GNN-Research
My future research
CyC2018/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计
halfrost/LeetCode-Go
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
krahets/LeetCode-Book
《剑指 Offer》 Python, Java, C++ 解题代码,LeetBook《图解算法数据结构》配套代码仓
changgyhub/leetcode_101
LeetCode 101:和你一起你轻松刷题(C++)
facebookresearch/ssl-relation-prediction
Simple yet SoTA Knowledge Graph Embeddings.
andreamad8/Universal-Transformer-Pytorch
Implementation of Universal Transformer in Pytorch
tkipf/pygcn
Graph Convolutional Networks in PyTorch
yao8839836/kg-bert
KG-BERT: BERT for Knowledge Graph Completion
haseebs/OWE
Pytorch code for An Open-World Extension to Knowledge Graph Completion Models (AAAI 2019)
zjunlp/MKGformer
[SIGIR 2022] Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
wangmengsd/RSME
seukgcode/MELBench
Multimodal entity linking (MEL) aims to utilize multimodal information to map mentions to corresponding entities defined in knowledge bases. We release three MEL datasets: Weibo-MEL, Wikidata-MEL and Richpedia-MEL, containing 25,602, 18,880 and 17,806 samples from social media, encyclopedia and multimodal knowledge graphs respectively. A MEL dataset construction approach is proposed, including five stages: multimodal information extraction, mention extraction, entity extraction, triple construction and dataset construction. Experiment results demonstrate the usability of the datasets and the distinguishability between baseline models.
pliang279/awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
mniepert/mmkb
Several data modalities for KBs (visual, numerical, temporal, etc.)
jiasenlu/HieCoAttenVQA
pouyapez/mkbe
Embedding Multimodal Relational Data for Knowledge Base Completion
LYuhang/Trans-Implementation
Implement of TransE, TransH, KG2E with pytorch