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Investigation of chemical structure recognition by encoder-decoder
  models in learning progress

Investigation of chemical structure recognition by encoder-decoder models in learning progress

24 October 2022
Katsuhisa Morita
T. Mizuno
Hiroyuki Kusuhara
ArXivPDFHTML

Papers citing "Investigation of chemical structure recognition by encoder-decoder models in learning progress"

12 / 12 papers shown
Title
Interpreting Deep Learning Models in Natural Language Processing: A
  Review
Interpreting Deep Learning Models in Natural Language Processing: A Review
Xiaofei Sun
Diyi Yang
Xiaoya Li
Tianwei Zhang
Yuxian Meng
Han Qiu
Guoyin Wang
Eduard H. Hovy
Jiwei Li
31
46
0
20 Oct 2021
Generative Chemical Transformer: Neural Machine Learning of Molecular
  Geometric Structures from Chemical Language via Attention
Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention
Hyunseung Kim
Jonggeol Na
Won Bo Lee
44
47
0
27 Feb 2021
How Neural Networks Extrapolate: From Feedforward to Graph Neural
  Networks
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu
Mozhi Zhang
Jingling Li
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
MLT
101
312
0
24 Sep 2020
Molecule Attention Transformer
Molecule Attention Transformer
Lukasz Maziarka
Tomasz Danel
Slawomir Mucha
Krzysztof Rataj
Jacek Tabor
Stanislaw Jastrzebski
60
169
0
19 Feb 2020
Optuna: A Next-generation Hyperparameter Optimization Framework
Optuna: A Next-generation Hyperparameter Optimization Framework
Takuya Akiba
Shotaro Sano
Toshihiko Yanase
Takeru Ohta
Masanori Koyama
527
5,769
0
25 Jul 2019
UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
154
9,390
0
09 Feb 2018
In silico generation of novel, drug-like chemical matter using the LSTM
  neural network
In silico generation of novel, drug-like chemical matter using the LSTM neural network
P. Ertl
Richard A. Lewis
E. Martin
V. Polyakov
48
59
0
20 Dec 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
147
2,921
0
07 Oct 2016
Generating Sentences from a Continuous Space
Generating Sentences from a Continuous Space
Samuel R. Bowman
Luke Vilnis
Oriol Vinyals
Andrew M. Dai
Rafal Jozefowicz
Samy Bengio
DRL
100
2,358
0
19 Nov 2015
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David Duvenaud
D. Maclaurin
J. Aguilera-Iparraguirre
Rafael Gómez-Bombarelli
Timothy D. Hirzel
Alán Aspuru-Guzik
Ryan P. Adams
GNN
191
3,345
0
30 Sep 2015
On the Properties of Neural Machine Translation: Encoder-Decoder
  Approaches
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho
B. V. Merrienboer
Dzmitry Bahdanau
Yoshua Bengio
AI4CE
AIMat
217
6,772
0
03 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
505
27,263
0
01 Sep 2014
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