Physics-Informed Neural Network Super Resolution for Advection-Diffusion Models

Evolutions in 3D numerical relativity using fixed mesh refinement

Erik Schnetter, Scott H. Hawley, and Ian Hawke · 2004

Earlier work this paper cites.

Kranc: a Mathematica package to generate numerical codes for tensorial evolution equations

Sascha Husa, Ian Hinder, and Christiane Lechner · 2006

Earlier work this paper cites.

The computational future for climate and earth system models: on the path to petaflop and beyond

Lawrence Buja Washington, Warren M. and Anthony Craig · 2009

Earlier work this paper cites.

The Einstein Toolkit: A Community Computational Infrastructure for Relativistic Astrophysics

Frank Löffler, Joshua Faber, Eloisa Bentivegna, Tanja Bode, Peter Diener, Roland Haas, Ian Hinder, Bruno C. Mundim, Christian D. Ott, Erik Schnetter, Gabrielle Allen, Manuela Campanelli, and Pablo Laguna · 2012

Earlier work this paper cites.

Learning a deep convolutional network for image super-resolution

Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014

Earlier work this paper cites.

Generative adversarial nets

Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014

Earlier work this paper cites.

Single image super-resolution from transformed self-exemplars

Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja · 2015

Earlier work this paper cites.

Accurate image super-resolution using very deep convolutional networks

Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016

Cited alongside, same era.

Deeply-recursive convolutional network for image super-resolution

Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016

Cited alongside, same era.

Photo-realistic single image super-resolution using a generative adversarial network

Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017

Cited alongside, same era.

Enhanced deep residual networks for single image super-resolution

Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017

Cited alongside, same era.

Image super-resolution via deep recursive residual network

Ying Tai, Jian Yang, and Xiaoming Liu · 2017

Cited alongside, same era.

Memnet: A persistent memory network for image restoration

Ntire 2017 challenge on single image super-resolution: Methods and results

Radu Timofte, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, and Lei Zhang · 2017

Later among the works it cites.

Esrgan: Enhanced super-resolution generative adversarial networks

Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018

Later among the works it cites.

Super-resolution reconstruction of turbulent flows with machine learning

Original

Kai Fukami, Koji Fukagata, and Kunihiko Taira · 2018

Later among the works it cites.

A scientific algorithm to simultaneously retrieve carbon monoxide and methane from tropomi onboard sentinel-5 precursor

Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John Burrows, Tobias Borsdorff, and Nicholas M. Deutscher · 2019

Later among the works it cites.

Second-order attention network for single image super-resolution

Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, and Lei Zhang · 2019

Later among the works it cites.