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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"

50 / 106 papers shown
Title
Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and
  Attention Mechanism Approach for Heterogeneous Graph-Structured Data
Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and Attention Mechanism Approach for Heterogeneous Graph-Structured Data
Jinghan Huang
Qiufeng Chen
Yijun Bian
Pengli Zhu
Nanguang Chen
Moo K. Chung
Anqi Qiu
30
0
0
11 Mar 2024
Jet Discrimination with Quantum Complete Graph Neural Network
Jet Discrimination with Quantum Complete Graph Neural Network
Yi-An Chen
Kai-Feng Chen
GNN
18
1
0
08 Mar 2024
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural
  Networks
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
Lisa Schneckenreiter
Richard Freinschlag
Florian Sestak
Johannes Brandstetter
G. Klambauer
Andreas Mayr
20
4
0
07 Mar 2024
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation
  to Account for Sampling Bias in Ecological Networks
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
Emré Anakok
Pierre Barbillon
Colin Fontaine
Elisa Thébault
CML
19
2
0
04 Mar 2024
Text-Guided Molecule Generation with Diffusion Language Model
Text-Guided Molecule Generation with Diffusion Language Model
Haisong Gong
Qiang Liu
Shu Wu
Liang Wang
27
12
0
20 Feb 2024
Position: Topological Deep Learning is the New Frontier for Relational
  Learning
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou
Tolga Birdal
Michael M. Bronstein
Gunnar Carlsson
Justin Curry
...
Petar Velickovic
Bei Wang
Yusu Wang
Guo-Wei Wei
Ghada Zamzmi
AI4CE
54
25
0
14 Feb 2024
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force
  Fields
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields
Joshua A. Vita
Amit Samanta
Fei Zhou
Vincenzo Lordi
16
2
0
01 Feb 2024
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening,
  and Condensation
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation
Mohammad Hashemi
Shengbo Gong
Juntong Ni
Wenqi Fan
B. A. Prakash
Wei-dong Jin
DD
59
39
0
29 Jan 2024
Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based
  Latent Dynamics Model
Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Latent Dynamics Model
Peng Zhou
Pai Zheng
Jiaming Qi
Chenxi Li
Chenguang Yang
D. Navarro-Alarcon
Jia Pan
AI4CE
15
1
0
21 Jan 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
Structure-based out-of-distribution (OOD) materials property prediction:
  a benchmark study
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study
Sadman Sadeed Omee
Nihang Fu
Rongzhi Dong
Ming Hu
Jianjun Hu
OOD
21
17
0
16 Jan 2024
Molecular Hypergraph Neural Networks
Molecular Hypergraph Neural Networks
Junwu Chen
Philippe Schwaller
GNN
26
10
0
20 Dec 2023
Predicting and Interpreting Energy Barriers of Metallic Glasses with
  Graph Neural Networks
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li
Shichang Zhang
Longwen Tang
Mathieu Bauchy
Yizhou Sun
AI4CE
35
0
0
08 Dec 2023
PyTorch Geometric High Order: A Unified Library for High Order Graph
  Neural Network
PyTorch Geometric High Order: A Unified Library for High Order Graph Neural Network
Xiyuan Wang
Muhan Zhang
AI4CE
13
3
0
28 Nov 2023
A Universal Framework for Accurate and Efficient Geometric Deep Learning
  of Molecular Systems
A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems
Shuo-feng Zhang
Yang Liu
Lei Xie
AI4CE
GNN
PINN
24
9
0
19 Nov 2023
Graph Neural Networks for Pressure Estimation in Water Distribution
  Systems
Graph Neural Networks for Pressure Estimation in Water Distribution Systems
Huy Truong
Andres Tello
Alexander Lazovik
Victoria Degeler
20
7
0
17 Nov 2023
Evaluating Neighbor Explainability for Graph Neural Networks
Evaluating Neighbor Explainability for Graph Neural Networks
Oscar Llorente
Rana Fawzy
Jared Keown
Michal Horemuz
Péter Vaderna
Sándor Laki
Roland Kotroczó
Rita Csoma
János Márk Szalai-Gindl
6
0
0
14 Nov 2023
Equivariance Is Not All You Need: Characterizing the Utility of
  Equivariant Graph Neural Networks for Particle Physics Tasks
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks
S. Thais
D. Murnane
AI4CE
18
4
0
06 Nov 2023
Hypergraph Echo State Network
Hypergraph Echo State Network
Justin Lien
GNN
16
0
0
16 Oct 2023
Probabilistically Rewired Message-Passing Neural Networks
Probabilistically Rewired Message-Passing Neural Networks
Chendi Qian
Andrei Manolache
Kareem Ahmed
Zhe Zeng
Guy Van den Broeck
Mathias Niepert
Christopher Morris
26
11
0
03 Oct 2023
Graph Neural Network-based EEG Classification: A Survey
Graph Neural Network-based EEG Classification: A Survey
D. Klepl
Min Wu
F. He
33
21
0
03 Oct 2023
Machine Learning for Practical Quantum Error Mitigation
Machine Learning for Practical Quantum Error Mitigation
Haoran Liao
Derek S. Wang
Iskandar Sitdikov
Ciro Salcedo
Alireza Seif
Zlatko K. Minev
AAML
AI4CE
6
31
0
29 Sep 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
Investigating the Interplay between Features and Structures in Graph
  Learning
Investigating the Interplay between Features and Structures in Graph Learning
Daniele Castellana
Federico Errica
15
3
0
18 Aug 2023
Exploiting Code Symmetries for Learning Program Semantics
Exploiting Code Symmetries for Learning Program Semantics
Kexin Pei
Weichen Li
Qirui Jin
Shuyang Liu
Scott Geng
Lorenzo Cavallaro
Junfeng Yang
Suman Jana
23
4
0
07 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
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Filip Ekstrom Kelvinius
D. Georgiev
Artur P. Toshev
Johannes Gasteiger
16
6
0
26 Jun 2023
Substitutional Alloying Using Crystal Graph Neural Networks
Substitutional Alloying Using Crystal Graph Neural Networks
Dario Massa
Daniel Cie'sliñski
A. Naghdi
Stefanos Papanikolaou
AI4CE
11
1
0
19 Jun 2023
Analysis and Approximate Inference of Large Random Kronecker Graphs
Analysis and Approximate Inference of Large Random Kronecker Graphs
Zhenyu Liao
Yuanqian Xia
Chengmei Niu
Yong Xiao
61
0
0
14 Jun 2023
Fine-grained Expressivity of Graph Neural Networks
Fine-grained Expressivity of Graph Neural Networks
Jan Böker
Ron Levie
Ningyuan Huang
Soledad Villar
Christopher Morris
15
20
0
06 Jun 2023
Mitigating Molecular Aggregation in Drug Discovery with Predictive
  Insights from Explainable AI
Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI
Hunter Sturm
Jonas Teufel
Kaitlin A. Isfeld
Pascal Friederich
Rebecca Davis
11
2
0
03 Jun 2023
Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient
  Prediction
Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient Prediction
Jan G. Rittig
Kobi C. Felton
A. Lapkin
Alexander Mitsos
AI4CE
12
13
0
31 May 2023
Differentiable graph-structured models for inverse design of lattice
  materials
Differentiable graph-structured models for inverse design of lattice materials
Dominik Dold
Derek Aranguren van Egmond
AI4CE
16
12
0
11 Apr 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
Equivariant Parameter Sharing for Porous Crystalline Materials
Equivariant Parameter Sharing for Porous Crystalline Materials
Marko Petković
Pablo Romero-Marimon
Vlado Menkovski
Sofía Calero
19
1
0
04 Apr 2023
Geometric Deep Learning for Molecular Crystal Structure Prediction
Geometric Deep Learning for Molecular Crystal Structure Prediction
Michael Kilgour
J. Rogal
M. Tuckerman
8
15
0
17 Mar 2023
Invariant Layers for Graphs with Nodes of Different Types
Invariant Layers for Graphs with Nodes of Different Types
Dmitry Rybin
Ruoyu Sun
Zhimin Luo
18
0
0
27 Feb 2023
Attending to Graph Transformers
Attending to Graph Transformers
Luis Muller
Mikhail Galkin
Christopher Morris
Ladislav Rampášek
44
84
0
08 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property
  Prediction
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction
Dominic Masters
Josef Dean
Kerstin Klaser
Zhiyi Li
Sam Maddrell-Mander
...
D. Beker
Andrew Fitzgibbon
Shenyang Huang
Ladislav Rampášek
Dominique Beaini
28
8
0
06 Feb 2023
Complete Neural Networks for Complete Euclidean Graphs
Complete Neural Networks for Complete Euclidean Graphs
Snir Hordan
Tal Amir
S. Gortler
Nadav Dym
3DPC
6
5
0
31 Jan 2023
Artificial intelligence approaches for materials-by-design of energetic
  materials: state-of-the-art, challenges, and future directions
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions
Joseph B. Choi
Phong C. H. Nguyen
O. Sen
H. Udaykumar
Stephen Seung-Yeob Baek
PINN
AI4CE
14
11
0
15 Nov 2022
Physical Pooling Functions in Graph Neural Networks for Molecular
  Property Prediction
Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction
Artur M. Schweidtmann
Jan G. Rittig
Jana M. Weber
Martin Grohe
Manuel Dahmen
K. Leonhard
Alexander Mitsos
6
24
0
27 Jul 2022
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
204
224
0
12 Oct 2021
Boundary Graph Neural Networks for 3D Simulations
Boundary Graph Neural Networks for 3D Simulations
Andreas Mayr
Sebastian Lehner
A. Mayrhofer
C. Kloss
Sepp Hochreiter
Johannes Brandstetter
AI4CE
4
32
0
21 Jun 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
218
498
0
20 Oct 2020
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