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Automated patent extraction powers generative modeling in focused
  chemical spaces

Automated patent extraction powers generative modeling in focused chemical spaces

14 March 2023
Akshay Subramanian
Kevin P. Greenman
Alexis Gervaix
Tzuhsiung Yang
Rafael Gómez-Bombarelli
ArXivPDFHTML

Papers citing "Automated patent extraction powers generative modeling in focused chemical spaces"

5 / 5 papers shown
Title
Biases in In Silico Evaluation of Molecular Optimization Methods and
  Bias-Reduced Evaluation Methodology
Biases in In Silico Evaluation of Molecular Optimization Methods and Bias-Reduced Evaluation Methodology
Hiroshi Kajino
Kohei Miyaguchi
Takayuki Osogami
59
1
0
28 Jan 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
131
142
0
06 Dec 2021
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
194
633
0
29 Nov 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,338
0
12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
175
1,778
0
02 Mar 2017
1