Kai Fukami

Computational Mechanics · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 25 citations into it; #9,914 of 10,001 by trust here, #6,287 by citations
• Statistical and Nonlinear Physics — 25 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Model Architectures — 10 citations into it
• Artificial Intelligence — 7 citations into it
• Optimization & Training — 5 citations into it

Whom Kai Fukami trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Tim Colonius
2. Kunihiko Taira
3. Lutz Prechelt
4. Diederik P. Kingma
5. Geoffrey E. Hinton
6. Yann LeCun
7. Vinod Nair
8. Jimmy Ba
9. Steven L. Brunton
10. Yoshua Bengio

Who trusts Kai Fukami overall

1. Bo Liu
2. Steven L. Brunton
3. Jiupeng Tang
4. Ricardo Vinuesa

Papers from Kai Fukami's perspective

Ordered by how strongly the researchers Kai Fukami trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Machine-learning-based spatio-temporal super resolution reconstruction of turbulent flows (2020) — 340 citations
• Nonlinear mode decomposition with convolutional neural networks for fluid dynamics (2019) — 341 citations
• Super-resolution reconstruction of turbulent flows with machine learning (2018) — 788 citations