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FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using
  Hessian-Free Trust-Region Methods
v1v2 (latest)

FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods

28 October 2019
Nur Sila Gulgec
Zheng Shi
Neil Deshmukh
S. Pakzad
Martin Takáč
ArXiv (abs)PDFHTML

Papers citing "FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods"

4 / 4 papers shown
Title
A spatio-temporal LSTM model to forecast across multiple temporal and
  spatial scales
A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales
Yihao Hu
Fearghal O'Donncha
Paul Palmes
M. Burke
R. Filgueira
Jon Grant
AI4TS
71
44
0
26 Aug 2021
The Discovery of Dynamics via Linear Multistep Methods and Deep
  Learning: Error Estimation
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation
Q. Du
Yiqi Gu
Haizhao Yang
Chao Zhou
66
20
0
21 Mar 2021
Discovery of Dynamics Using Linear Multistep Methods
Discovery of Dynamics Using Linear Multistep Methods
Rachael Keller
Q. Du
83
36
0
29 Dec 2019
Using Deep Learning to Extend the Range of Air-Pollution Monitoring and
  Forecasting
Using Deep Learning to Extend the Range of Air-Pollution Monitoring and Forecasting
Philipp Haehnel
Jakub Mareˇcek
Julien Monteil
Fearghal O'Donncha
AI4CE
29
39
0
22 Oct 2018
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