Naoya Takeishi
Statistical and Nonlinear Physics · 2017
A researcher in the Science corpus: 1 paper; trusts 34 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 22 citations into it; #3,770 of 10,127 by trust here, #5,200 by citations
- Artificial Intelligence — 16 citations into it
- Computational Mechanics — 11 citations into it; #4,108 of 10,001 by trust here, #5,350 by citations
- Computer Vision and Pattern Recognition — 7 citations into it
Whom Naoya Takeishi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Steven L. Brunton
- J. Nathan Kutz
- Clarence W. Rowley
- Igor Mezi'c
- Chih-Jen Lin
- Floris Takens
- Diederik P. Kingma
- Joshua L. Proctor
- Peter J. Schmid
- Sergey Ioffe
Who trusts Naoya Takeishi overall
- Hao Wu
- Zijie Li
- Enoch Yeung
- Jared D. Willard
- Kathleen P. Champion
- Jeremy Morton
- Steven L. Brunton
- Christopher Rackauckas
- Frank No'e
- Bethany Lusch
Papers from Naoya Takeishi's perspective
Ordered by how strongly the researchers Naoya Takeishi trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition (2017) — 468 citations