Statements (23)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
graph-based deep learning model
|
| gptkbp:approach |
policy gradient
|
| gptkbp:arXivID |
1806.02473
|
| gptkbp:citation |
2018
10.48550/arXiv.1806.02473 Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation |
| gptkbp:developedBy |
gptkb:Rex_Ying
gptkb:Jure_Leskovec gptkb:Vijay_Pande Bowen Liu Jiaxuan You |
| gptkbp:fullName |
Graph Convolutional Policy Network
|
| https://www.w3.org/2000/01/rdf-schema#label |
GCPN
|
| gptkbp:input |
molecular graph
|
| gptkbp:method |
gptkb:reinforcement_learning
|
| gptkbp:output |
molecular graph
|
| gptkbp:platform |
deep reinforcement learning
|
| gptkbp:publishedIn |
gptkb:ICML_2018
|
| gptkbp:usedFor |
molecular graph generation
|
| gptkbp:usedIn |
computational chemistry
drug discovery |
| gptkbp:bfsParent |
gptkb:Stephen_Sims
|
| gptkbp:bfsLayer |
8
|