Akira Kunimatsu

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Model Architectures — 5 citations into it

Whom Akira Kunimatsu trusts overall

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

1. Yoshua Bengio
2. R. Caruana
3. Geoffrey E. Hinton
4. Sergey Ioffe
5. Vinod Nair
6. Christian Szegedy
7. John C. Duchi

Papers from Akira Kunimatsu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Going deeper with convolutions
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Dropout: a simple way to prevent neural networks from overfitting
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Rectified Linear Units Improve Restricted Boltzmann Machines
9. Long Short-Term Memory
10. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Their papers

• Deep learning with convolutional neural network in radiology (2018) — 346 citations