molecular generation
13
Aug
Generative Models for Graphs
#CellStratAILab #disrupt4.0 #WeCreateAISuperstars Recently, our AI Lab Researcher Gouthaman Asokan presented an amazing session on Generative Models for Graphs. This is part of our webinar series on Graphs and Graph Neural Networks. Graph is a nonlinear data structure consisting of nodes and edges. Widely used in applications like Physical system interactions, Knowledge graphs, Molecular interactions, Transportation […]
Tags:
bernoulli distribution,
categorical distribution,
deep generative model for graph,
DGMG,
generative model,
generative modelling,
GrammarVAE,
graph embedding,
graph grammar,
graph neural network,
graph propagation,
molecular generation,
Simplified Molecular Input Line Entry System,
SMILES,
synthentic graph,
synthetic graph,
teacher forcing,