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Graph neural networks for materials science and chemistry

Graph neural networks for materials science and chemistry

5 August 2022
Patrick Reiser
Marlen Neubert
André Eberhard
Luca Torresi
Chen Zhou
Chen Shao
Houssam Metni
Clint van Hoesel
Henrik Schopmans
T. Sommer
Pascal Friederich
    GNN
    AI4CE
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Papers citing "Graph neural networks for materials science and chemistry"

25 / 25 papers shown
Title
SA-GAT-SR: Self-Adaptable Graph Attention Networks with Symbolic Regression for high-fidelity material property prediction
SA-GAT-SR: Self-Adaptable Graph Attention Networks with Symbolic Regression for high-fidelity material property prediction
Liu Junchi
Tang Ying
Tretiak Sergei
Duan Wenhui
Zhou Liujiang
33
0
0
01 May 2025
Inference-friendly Graph Compression for Graph Neural Networks
Inference-friendly Graph Compression for Graph Neural Networks
Yangxin Fan
Haolai Che
Yinghui Wu
GNN
46
0
0
17 Apr 2025
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery
Shuyi Jia
Shitij Govil
Manav Ramprasad
Victor Fung
AI4CE
59
1
0
03 Mar 2025
Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers
Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers
Markus J. Buehler
AI4CE
35
1
0
04 Jan 2025
GraphXForm: Graph transformer for computer-aided molecular design
GraphXForm: Graph transformer for computer-aided molecular design
Jonathan Pirnay
Jan G. Rittig
Alexander B. Wolf
Martin Grohe
Jakob Burger
Alexander Mitsos
D. G. Grimm
AI4CE
49
1
0
03 Nov 2024
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
Yanpeng Ye
Jie Ren
Shaozhou Wang
Yuwei Wan
Haofen Wang
B. Hoex
Tong Xie
Tong Xie
Wenjie Zhang
AI4CE
35
1
0
03 Apr 2024
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks
Philip Matthias Winter
M. Wimmer
David Major
Dimitrios Lenis
Astrid Berg
Theresa Neubauer
Gaia Romana De Paolis
Johannes Novotny
Sophia Ulonska
Katja Bühler
34
0
0
18 Mar 2024
Disentangled Condensation for Large-scale Graphs
Disentangled Condensation for Large-scale Graphs
Zhenbang Xiao
Shunyu Liu
Yu Wang
Tongya Zheng
Mingli Song
Mingli Song
Tongya Zheng
DD
69
6
0
18 Jan 2024
Hypergraph Echo State Network
Hypergraph Echo State Network
Justin Lien
GNN
11
0
0
16 Oct 2023
Materials Informatics Transformer: A Language Model for Interpretable
  Materials Properties Prediction
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction
Hongshuo Huang
Rishikesh Magar
Chang Xu
A. Farimani
AI4CE
25
4
0
30 Aug 2023
Prot2Text: Multimodal Protein's Function Generation with GNNs and
  Transformers
Prot2Text: Multimodal Protein's Function Generation with GNNs and Transformers
Hadi Abdine
Michail Chatzianastasis
Costas Bouyioukos
Michalis Vazirgiannis
26
38
0
25 Jul 2023
High Accuracy Uncertainty-Aware Interatomic Force Modeling with
  Equivariant Bayesian Neural Networks
High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks
Tim Rensmeyer
Benjamin Craig
D. Kramer
Oliver Niggemann
BDL
11
3
0
05 Apr 2023
FastFlows: Flow-Based Models for Molecular Graph Generation
FastFlows: Flow-Based Models for Molecular Graph Generation
Nathan C. Frey
V. Gadepally
Bharath Ramsundar
14
12
0
28 Jan 2022
Simulation Intelligence: Towards a New Generation of Scientific Methods
Simulation Intelligence: Towards a New Generation of Scientific Methods
Alexander Lavin
D. Krakauer
Hector Zenil
Justin Emile Gottschlich
Tim Mattson
...
A. Hanuka
Manuela Veloso
Samuel A. Assefa
Stephan Zheng
Avi Pfeffer
40
102
0
06 Dec 2021
Crystal Diffusion Variational Autoencoder for Periodic Material
  Generation
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Tian Xie
Xiang Fu
O. Ganea
Regina Barzilay
Tommi Jaakkola
DiffM
BDL
196
224
0
12 Oct 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and
  Nonlocal Effects
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects
Oliver T. Unke
Stefan Chmiela
M. Gastegger
Kristof T. Schütt
H. E. Sauceda
K. Müller
142
242
0
01 May 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate
  Interatomic Potentials
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials
Simon L. Batzner
Albert Musaelian
Lixin Sun
Mario Geiger
J. Mailoa
M. Kornbluth
N. Molinari
Tess E. Smidt
Boris Kozinsky
188
1,218
0
08 Jan 2021
Symmetry-adapted graph neural networks for constructing molecular
  dynamics force fields
Symmetry-adapted graph neural networks for constructing molecular dynamics force fields
Zun Wang
Chong Wang
Sibo Zhao
Shiqiao Du
Yong Xu
B. Gu
W. Duan
AI4CE
21
14
0
08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
L. Chanussot
Abhishek Das
Siddharth Goyal
Thibaut Lavril
Muhammed Shuaibi
...
Brandon M. Wood
Junwoong Yoon
Devi Parikh
C. L. Zitnick
Zachary W. Ulissi
207
370
0
20 Oct 2020
Coarse Graining Molecular Dynamics with Graph Neural Networks
Coarse Graining Molecular Dynamics with Graph Neural Networks
B. Husic
N. Charron
Dominik Lemm
Jiang Wang
Adria Pérez
...
Yaoyi Chen
Simon Olsson
Gianni de Fabritiis
Frank Noé
C. Clementi
AI4CE
29
156
0
22 Jul 2020
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
181
878
0
07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
208
1,329
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
154
1,748
0
02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
234
1,801
0
25 Nov 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
231
3,202
0
24 Nov 2016
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