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Differentiable graph-structured models for inverse design of lattice
  materials
v1v2 (latest)

Differentiable graph-structured models for inverse design of lattice materials

11 April 2023
Dominik Dold
Derek Aranguren van Egmond
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Differentiable graph-structured models for inverse design of lattice materials"

13 / 13 papers shown
Title
A Generalist Neural Algorithmic Learner
A Generalist Neural Algorithmic Learner
Borja Ibarz
Vitaly Kurin
George Papamakarios
Kyriacos Nikiforou
Mehdi Abbana Bennani
...
Andreea Deac
Beatrice Bevilacqua
Yaroslav Ganin
Charles Blundell
Petar Velivcković
OOD
92
54
0
22 Sep 2022
Learning Mesh-Based Simulation with Graph Networks
Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff
Meire Fortunato
Alvaro Sanchez-Gonzalez
Peter W. Battaglia
AI4CE
84
806
0
07 Oct 2020
Molecular Property Prediction: A Multilevel Quantum Interactions
  Modeling Perspective
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective
Chengqiang Lu
Qi Liu
Chao Wang
Zhenya Huang
Peize Lin
Lixin He
AI4CE
70
193
0
25 Jun 2019
GNNExplainer: Generating Explanations for Graph Neural Networks
GNNExplainer: Generating Explanations for Graph Neural Networks
Rex Ying
Dylan Bourgeois
Jiaxuan You
Marinka Zitnik
J. Leskovec
LLMAG
155
1,334
0
10 Mar 2019
Surrogate Gradient Learning in Spiking Neural Networks
Surrogate Gradient Learning in Spiking Neural Networks
Emre Neftci
Hesham Mostafa
Friedemann Zenke
106
1,244
0
28 Jan 2019
Accelerated physical emulation of Bayesian inference in spiking neural
  networks
Accelerated physical emulation of Bayesian inference in spiking neural networks
Á. F. Kungl
Sebastian Schmitt
Johann Klähn
Paul Müller
A. Baumbach
...
V. Karasenko
Andreas Grübl
Johannes Schemmel
K. Meier
Mihai A. Petrovici
53
36
0
06 Jul 2018
Dynamic Graph CNN for Learning on Point Clouds
Dynamic Graph CNN for Learning on Point Clouds
Yue Wang
Yongbin Sun
Ziwei Liu
Sanjay E. Sarma
M. Bronstein
Justin Solomon
GNN3DPC
265
6,179
0
24 Jan 2018
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
523
15,375
0
07 Jun 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
600
7,500
0
04 Apr 2017
Modeling Relational Data with Graph Convolutional Networks
Modeling Relational Data with Graph Convolutional Networks
Michael Schlichtkrull
Thomas Kipf
Peter Bloem
Rianne van den Berg
Ivan Titov
Max Welling
GNN
196
4,844
0
17 Mar 2017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on
  the BrainScaleS Wafer-Scale System
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Sebastian Schmitt
Johann Klaehn
G. Bellec
Andreas Grübl
Maurice Guettler
...
Robert Legenstein
Wolfgang Maass
Christian Mayr
Johannes Schemmel
K. Meier
56
138
0
06 Mar 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
693
29,220
0
09 Sep 2016
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
S. K. Esser
P. Merolla
John V. Arthur
A. Cassidy
R. Appuswamy
...
Pallab Datta
A. Amir
B. Taba
M. Flickner
D. Modha
3DH
67
718
0
28 Mar 2016
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