LOGIKA & PENALARAN DALAM WEB SEMANTIK
0%
Previous
Course data
General
Informasi Umum tentang perkuliahan ini
Introduction to Graph Machine Learning
week01-Introduction
week01-Introduction to SW
video about introduction
Week02-Feature engineering in traditional ML
week02-Feature engineering in traditional ML
Assignment week 01
Assignment week 01 learning node embeddings
Week03-Node Embeddings
week03-nodeEmbedding
a video about node embedding
Week04-Graph Neural Network
week04-Graph Neural Network
Week05-5. A General Perspective on GNNs
Week05-5. A General Perspective on GNNs
a video for introducing GNN
week06-GNN Augmentation
week06-GNN Augmentation
a video about GNN in more depth
Week7-How expressive are GNN
Week7-How expressive are GNN
Label propagation on graph
week08-label propagation on graph
Assignment week 8
week09-Machine Learning with Heterogeneous Graphs
week09-Machine Learning with Heterogeneous Graphs
a video about Heterogeneous Graphs
week10-Knowledge Graph Embedding
week10-KG Embedding
a video about KGC with Embedding
Assignment week 10 (KGE)
week11-Reasoning over Knowledge Graphs
week11a-Reasoning over Knowledge Graphs
a blog tutorial in AAAI 22 about reasoning over KGs
a video about week 11
assignment week 11
week12. GNNs for Recommender Systems
a blog post about GNN for RS
week13. Deep Generative Models for Graphs
a video about week13: Deep Generative Models
week13-Deep Generative Models for Graph
week14. Scaling Up GNNs to Large Graphs
a video about week 14
week15. GNNs and Transformers
a video about GNN and Transformers
a slide about GNN and transformers
Assignment week 15 (https://graphormer.readthedocs.io/en/latest/Tutorisals.html)
Next
Side panel
English (en)
Bahasa Indonesia (id)
English (en)
Enter your search query
Log in
CII7B3-31002
Home
Skip to main content
Course info
Home
Courses
FAKULTAS INFORMATIKA (FIF)
PRODI S2 INFORMATIKA (FIF)
CII7B3-31002
Summary
LOGIKA & PENALARAN DALAM WEB SEMANTIK
Teacher:
KEMAS RAHMAT SALEH WIHARJA