|
gptkbp:instance_of
|
gptkb:microprocessor
|
|
gptkbp:bfsLayer
|
3
|
|
gptkbp:bfsParent
|
gptkb:philosopher
gptkb:lighthouse
|
|
gptkbp:applies_to
|
Recommendation Systems
Social Networks
Biological Networks
|
|
gptkbp:based_on
|
gptkb:television_channel
gptkb:Recurrent_Neural_Networks
Graph Theory
|
|
gptkbp:can_be
|
Complex Relationships
|
|
gptkbp:can_be_used_with
|
gptkb:streaming_service
gptkb:software_framework
Attention Mechanisms
|
|
gptkbp:controls
|
Irregular Data Structures
|
|
gptkbp:developed_by
|
gptkb:Max_Welling
gptkb:Thomas_Kipf
|
|
gptkbp:enhances
|
Feature Learning
|
|
gptkbp:has_programs
|
gptkb:viewpoint
gptkb:software
Chemoinformatics
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Graph Neural Networks
|
|
gptkbp:improves
|
Data Representation
|
|
gptkbp:is_a
|
gptkb:software_framework
|
|
gptkbp:is_challenged_by
|
Scalability Issues
Overfitting
Data Sparsity
|
|
gptkbp:is_evaluated_by
|
Accuracy
F1 Score
AUC-ROC
|
|
gptkbp:is_explored_in
|
Conferences
Academic Papers
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Library
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
Linear Algebra
Topology
Graph Theory
|
|
gptkbp:is_popular_in
|
gptkb:Research_Institute
Industry Applications
|
|
gptkbp:is_related_to
|
gptkb:physicist
gptkb:Artificial_Intelligence
gptkb:software_framework
|
|
gptkbp:is_supported_by
|
Industry Partnerships
Research Grants
Open Source Libraries
|
|
gptkbp:is_used_for
|
Graph Classification
Link Prediction
Node Classification
|
|
gptkbp:is_used_in
|
Fraud Detection
Recommendation Engines
Traffic Prediction
|
|
gptkbp:requires
|
Graph Structure
Edge Features
Node Features
|
|
gptkbp:training
|
Backpropagation
|
|
gptkbp:utilizes
|
Message Passing
|