Picture for Amir Jalilifard

Amir Jalilifard

Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior

Add code
Oct 06, 2020
Figure 1 for Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
Figure 2 for Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
Figure 3 for Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
Figure 4 for Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
Viaarxiv icon

Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding

Add code
May 15, 2020
Figure 1 for Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
Figure 2 for Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
Figure 3 for Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
Figure 4 for Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
Viaarxiv icon

Semantic Sensitive TF-IDF to Determine Word Relevance in Documents

Add code
Jan 06, 2020
Figure 1 for Semantic Sensitive TF-IDF to Determine Word Relevance in Documents
Figure 2 for Semantic Sensitive TF-IDF to Determine Word Relevance in Documents
Viaarxiv icon

Can NetGAN be improved by short random walks originated from dense vertices?

Add code
May 13, 2019
Figure 1 for Can NetGAN be improved by short random walks originated from dense vertices?
Figure 2 for Can NetGAN be improved by short random walks originated from dense vertices?
Figure 3 for Can NetGAN be improved by short random walks originated from dense vertices?
Figure 4 for Can NetGAN be improved by short random walks originated from dense vertices?
Viaarxiv icon