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Augmented Memory: Capitalizing on Experience Replay to Accelerate De
  Novo Molecular Design

Augmented Memory: Capitalizing on Experience Replay to Accelerate De Novo Molecular Design

10 May 2023
Jeff Guo
P. Schwaller
ArXiv (abs)PDFHTML

Papers citing "Augmented Memory: Capitalizing on Experience Replay to Accelerate De Novo Molecular Design"

18 / 18 papers shown
Title
Reinforced Genetic Algorithm for Structure-based Drug Design
Reinforced Genetic Algorithm for Structure-based Drug Design
Tianfan Fu
Wenhao Gao
Connor W. Coley
Jimeng Sun
86
55
0
28 Nov 2022
Faster and more diverse de novo molecular optimization with double-loop
  reinforcement learning using augmented SMILES
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES
E. Bjerrum
Christian Margreitter
Thomas Blaschke
Raquel Lopez-Rios de Castro
67
12
0
22 Oct 2022
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
298
30,149
0
01 Mar 2022
Keeping it Simple: Language Models can learn Complex Molecular
  Distributions
Keeping it Simple: Language Models can learn Complex Molecular Distributions
Daniel Flam-Shepherd
Kevin Zhu
A. Aspuru‐Guzik
215
148
0
06 Dec 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate
  Generation
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Emmanuel Bengio
Moksh Jain
Maksym Korablyov
Doina Precup
Yoshua Bengio
103
333
0
08 Jun 2021
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural
  Networks for Inverse Molecular Design
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
AkshatKumar Nigam
R. Pollice
Alán Aspuru-Guzik
70
53
0
07 Jun 2021
Revisiting Fundamentals of Experience Replay
Revisiting Fundamentals of Experience Replay
W. Fedus
Prajit Ramachandran
Rishabh Agarwal
Yoshua Bengio
Hugo Larochelle
Mark Rowland
Will Dabney
KELMOffRL
78
242
0
13 Jul 2020
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation
  Models
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
259
653
0
29 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design
GuacaMol: Benchmarking Models for De Novo Molecular Design
Nathan Brown
Marco Fiscato
Marwin H. S. Segler
Alain C. Vaucher
ELM
114
711
0
22 Nov 2018
Optimization of Molecules via Deep Reinforcement Learning
Optimization of Molecules via Deep Reinforcement Learning
Zhenpeng Zhou
S. Kearnes
Li Li
R. Zare
Patrick F. Riley
AI4CE
107
542
0
19 Oct 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
295
902
0
07 Jun 2018
MolGAN: An implicit generative model for small molecular graphs
MolGAN: An implicit generative model for small molecular graphs
Nicola De Cao
Thomas Kipf
GNNGAN
179
928
0
30 May 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
199
9,473
0
09 Feb 2018
Deep Reinforcement Learning for De-Novo Drug Design
Deep Reinforcement Learning for De-Novo Drug Design
Mariya Popova
Olexandr Isayev
Alexander Tropsha
93
1,031
0
29 Nov 2017
Objective-Reinforced Generative Adversarial Networks (ORGAN) for
  Sequence Generation Models
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
G. L. Guimaraes
Benjamín Sánchez-Lengeling
Carlos Outeiral
Pedro Luis Cunha Farias
Alán Aspuru-Guzik
GAN
85
525
0
30 May 2017
Molecular De Novo Design through Deep Reinforcement Learning
Molecular De Novo Design through Deep Reinforcement Learning
Marcus Olivecrona
T. Blaschke
Ola Engkvist
Hongming Chen
BDL
130
1,017
0
25 Apr 2017
Automatic chemical design using a data-driven continuous representation
  of molecules
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
176
2,939
0
07 Oct 2016
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
455
16,923
0
20 Dec 2013
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