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1711.07839
Cited By
Application of generative autoencoder in de novo molecular design
21 November 2017
T. Blaschke
Marcus Olivecrona
O. Engkvist
J. Bajorath
Hongming Chen
AI4CE
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Papers citing
"Application of generative autoencoder in de novo molecular design"
20 / 20 papers shown
Title
Learning to generate feasible graphs using graph grammars
Stefan Mautner
Rolf Backofen
Fabrizio Costa
43
0
0
10 Jan 2025
Overcoming Order in Autoregressive Graph Generation
Edo Cohen-Karlik
Eyal Rozenberg
Daniel Freedman
34
1
0
04 Feb 2024
Improving Molecule Properties Through 2-Stage VAE
Chenghui Zhou
Barnabás Póczós
DRL
28
1
0
06 Dec 2022
Computer-Aided Multi-Objective Optimization in Small Molecule Discovery
Jenna C. Fromer
Connor W. Coley
29
66
0
13 Oct 2022
Fast-Image2Point: Towards Real-Time Point Cloud Reconstruction of a Single Image using 3D Supervision
AmirHossein Zamani
A. Aghdam
K. Ghaffari
3DV
3DPC
27
1
0
20 Sep 2022
Artificial Intelligence in Drug Discovery: Applications and Techniques
Jianyuan Deng
Zhibo Yang
Iwao Ojima
Dimitris Samaras
Fusheng Wang
AI4TS
21
100
0
09 Jun 2021
Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design
Ryan-Rhys Griffiths
P. Schwaller
Alpha A. Lee
AI4CE
34
19
0
06 May 2021
Polygrammar: Grammar for Digital Polymer Representation and Generation
Minghao Guo
Wan Shou
L. Makatura
Timothy Erps
Michael Foshey
Wojciech Matusik
32
24
0
05 May 2021
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
G. Simm
Robert Pinsler
José Miguel Hernández-Lobato
AI4CE
18
82
0
18 Feb 2020
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas W. A. Gebauer
M. Gastegger
Kristof T. Schütt
26
201
0
02 Jun 2019
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy
Alexander Zhebrak
Benjamín Sánchez-Lengeling
Sergey Golovanov
Oktai Tatanov
...
Simon Johansson
Hongming Chen
Sergey I. Nikolenko
Alán Aspuru-Guzik
Alex Zhavoronkov
ELM
194
633
0
29 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design
Nathan Brown
Marco Fiscato
Marwin H. S. Segler
Alain C. Vaucher
ELM
44
691
0
22 Nov 2018
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction
P. Schwaller
Teodoro Laino
John McGuinness
A. Horváth
Constantine Bekas
A. Lee
25
719
0
06 Nov 2018
Optimization of Molecules via Deep Reinforcement Learning
Zhenpeng Zhou
S. Kearnes
Li Li
R. Zare
Patrick F. Riley
AI4CE
16
532
0
19 Oct 2018
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks
Clyde Fare
Lukas Turcani
Edward O. Pyzer-Knapp
24
13
0
17 Sep 2018
Latent Molecular Optimization for Targeted Therapeutic Design
Tristan Aumentado-Armstrong
15
41
0
05 Sep 2018
Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification
Alexandr A Kalinin
Gerald A. Higgins
Narathip Reamaroon
S. M. Reza Soroushmehr
Ari Allyn-Feuer
I. Dinov
Kayvan Najarian
B. Athey
OOD
36
122
0
25 Jan 2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model
Yibo Li
L. Zhang
Zhenming Liu
35
335
0
18 Jan 2018
Constrained Bayesian Optimization for Automatic Chemical Design
Ryan-Rhys Griffiths
José Miguel Hernández-Lobato
BDL
39
76
0
16 Sep 2017
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
26
2,885
0
07 Oct 2016
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