Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have... Z Guo,Z Wu,T Xiao,... - 《Machine Intelligence Research》 被引量: 0发表: 2024年 Graph Representation Learning for Predicting Diverse ...
@article{hu2020ogb, title={Open Graph Benchmark: Datasets for Machine Learning on Graphs}, author={Hu, Weihua and Fey, Matthias and Zitnik, Marinka and Dong, Yuxiao and Ren, Hongyu and Liu, Bowen and Catasta, Michele and Leskovec, Jure}, journal={arXiv preprint arXiv:2005.00687}, yea...
(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. CGCSTCD = China Graduate Contest on Smart-city Technology and Creative Design opencvmachine-learningcomputer-visionartificial-intelligencesupervised-learningartificial-neural-networkschinese...
The semantic foundation of these graphs provides the necessary description for reuse. In this paper, we focus on tabular data and how that can be integrated into a KG. Besides the tabular data itself, we leverage existing metadata and publications describing the datasets for the KG construction....
11,363 machine learning datasets 🔔 Share your dataset with the ML community! Filter by Modality Images 3070 Texts 2945 Videos 962 Audio 460 Medical 378 3D 358 Graphs 270 Time series 266 Tabular 239 Speech 188 RGB-D 183 Environment 142 Point cloud 127 Biomedical 117 LiDAR 89 RGB Video ...
ML Writing: Machine learning for copywriting, guide writing, book writing Deep Graphs: Learn Graph databases machine learning, RNNs, CNNs, Generative AI
Learning 45 Knowledge Graphs 45 Semantic Parsing 45 Hate Speech Detection 44 Object Recognition 44 Self-Supervised Learning 44 Visual Reasoning 44 Entity Linking 43 Machine Reading Comprehension 43 Misinformation 43 Scene Understanding 43 Time Series Forecasting 43 Zero-Shot Learning 43 Image Clustering ...
TUDataset: A collection of benchmark datasets for learning with graphs,程序员大本营,技术文章内容聚合第一站。
How to Implement Graph RAG Using Knowledge Graphs and Vector Databases A Step-by-Step Tutorial on Implementing Retrieval-Augmented Generation (RAG), Semantic Search, and Recommendations Sep 6 Takuma Seno in Towards Data Science Welcome to Deep Reinforcement Learning Part 1 : DQN ...
Utility Metrics:The resemblance metrics above assess the structural or static aspects of the synthetic data for a generic realism assessment. It has been shown that synthetic data undergo lesser loss of utility for machine learning tasks[54]and may perform high despite an average score on fidelity...