Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visualizing Deep Graph Generative Models for Drug Discovery   Drug discovery aims at designing novel molecules with specific desired
properties for clinical trials. Over past decades, drug discovery and
development have been a costly and time consuming process. Driven by big
chemical data and AI, deep generative models show great potential to accelerate
the drug discovery process. Existing works investigate different deep
generative frameworks for molecular generation, however, less attention has
been paid to the visualization tools to quickly demo and evaluate model's
results. Here, we propose a visualization framework which provides interactive
visualization tools to visualize molecules generated during the encoding and
decoding process of deep graph generative models, and provide real time
molecular optimization functionalities. Our work tries to empower black box AI
driven drug discovery models with some visual interpretabilities.

3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org