ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2205.08619
  4. Cited By
A graph representation of molecular ensembles for polymer property
  prediction

A graph representation of molecular ensembles for polymer property prediction

17 May 2022
Matteo Aldeghi
Connor W. Coley
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "A graph representation of molecular ensembles for polymer property prediction"

16 / 16 papers shown
Title
Copolymer Informatics with Multi-Task Deep Neural Networks
Copolymer Informatics with Multi-Task Deep Neural Networks
Christopher Kuenneth
W. Schertzer
R. Ramprasad
44
50
0
25 Mar 2021
Molecular representation learning with language models and
  domain-relevant auxiliary tasks
Molecular representation learning with language models and domain-relevant auxiliary tasks
Benedek Fabian
T. Edlich
H. Gaspar
Marwin H. S. Segler
Joshua Meyers
Marco Fiscato
Mohamed Ahmed
70
128
0
26 Nov 2020
Polymer Informatics: Current Status and Critical Next Steps
Polymer Informatics: Current Status and Critical Next Steps
Lihua Chen
G. Pilania
Rohit Batra
T. D. Huan
Chiho Kim
Christopher Kuenneth
R. Ramprasad
AI4CE
46
182
0
01 Nov 2020
Polymer Informatics with Multi-Task Learning
Polymer Informatics with Multi-Task Learning
Christopher Künneth
Arunkumar Chitteth Rajan
Huan Tran
Lihua Chen
Chiho Kim
R. Ramprasad
AI4CE
60
94
0
28 Oct 2020
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular
  Property Prediction
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Seyone Chithrananda
Gabriel Grand
Bharath Ramsundar
AI4CE
92
413
0
19 Oct 2020
Directional Message Passing for Molecular Graphs
Directional Message Passing for Molecular Graphs
Johannes Klicpera
Janek Groß
Stephan Günnemann
127
881
0
06 Mar 2020
Neural Message Passing on High Order Paths
Neural Message Passing on High Order Paths
Daniel Flam-Shepherd
Tony C Wu
Pascal Friederich
Alán Aspuru-Guzik
GNNAI4CE
100
49
0
24 Feb 2020
Machine learning on DNA-encoded libraries: A new paradigm for
  hit-finding
Machine learning on DNA-encoded libraries: A new paradigm for hit-finding
Kevin McCloskey
E. Sigel
S. Kearnes
L. Xue
Xia Tian
...
C. Hupp
Anthony D. Keefe
Christopher J. Mulhern
Ying Zhang
Patrick F. Riley
90
104
0
31 Jan 2020
Machine Learning for Scent: Learning Generalizable Perceptual
  Representations of Small Molecules
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
Benjamín Sánchez-Lengeling
Jennifer N. Wei
Brian K. Lee
R. C. Gerkin
Alán Aspuru-Guzik
Alexander B. Wiltschko
GNN
62
95
0
23 Oct 2019
Analyzing Learned Molecular Representations for Property Prediction
Analyzing Learned Molecular Representations for Property Prediction
Kevin Kaichuang Yang
Kyle Swanson
Wengong Jin
Connor W. Coley
Philipp Eiden
...
Andrew Palmer
Volker Settels
Tommi Jaakkola
K. Jensen
Regina Barzilay
109
1,323
0
02 Apr 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
1.1K
5,534
0
20 Dec 2018
Message-passing neural networks for high-throughput polymer screening
Message-passing neural networks for high-throughput polymer screening
Peter C. St. John
Caleb Phillips
Travis W. Kemper
A. N. Wilson
M. Crowley
M. Nimlos
R. Larsen
AI4CE
54
112
0
26 Jul 2018
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
598
7,496
0
04 Apr 2017
Discriminative Embeddings of Latent Variable Models for Structured Data
Discriminative Embeddings of Latent Variable Models for Structured Data
H. Dai
Bo Dai
Le Song
BDL
122
697
0
17 Mar 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes
Kevin McCloskey
Marc Berndl
Vijay S. Pande
Patrick F. Riley
GNN
154
1,449
0
02 Mar 2016
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
223
3,357
0
30 Sep 2015
1