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Forecasting the outcome of spintronic experiments with Neural Ordinary
  Differential Equations

Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations

23 July 2021
Xing Chen
Flavio Abreu Araujo
M. Riou
J. Torrejon
D. Ravelosona
W. Kang
Weisheng Zhao
Julie Grollier
D. Querlioz
ArXivPDFHTML

Papers citing "Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations"

6 / 6 papers shown
Title
High-order expansion of Neural Ordinary Differential Equations flows
High-order expansion of Neural Ordinary Differential Equations flows
Dario Izzo
Sebastien Origer
Giacomo Acciarini
F. Biscani
AI4CE
29
0
0
02 Apr 2025
NeuralMAG: Fast and Generalizable Micromagnetic Simulation with Deep
  Neural Nets
NeuralMAG: Fast and Generalizable Micromagnetic Simulation with Deep Neural Nets
Yunqi Cai
Jiangnan Li
Dong Wang
OOD
AI4CE
26
0
0
19 Oct 2024
Efficient, Accurate and Stable Gradients for Neural ODEs
Efficient, Accurate and Stable Gradients for Neural ODEs
Sam McCallum
James Foster
32
4
0
15 Oct 2024
A perspective on physical reservoir computing with nanomagnetic devices
A perspective on physical reservoir computing with nanomagnetic devices
D. Allwood
Matthew O. A. Ellis
David Griffin
T. Hayward
Luca Manneschi
...
Martin A. Trefzer
Eleni Vasilaki
G. Venkat
Ian T. Vidamour
Chester Wringe
17
40
0
09 Dec 2022
On the Forward Invariance of Neural ODEs
On the Forward Invariance of Neural ODEs
Wei Xiao
Tsun-Hsuan Wang
Ramin Hasani
Mathias Lechner
Yutong Ban
Chuang Gan
Daniela Rus
33
11
0
10 Oct 2022
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
130
424
0
10 Mar 2020
1