Hiromi Nakagawa

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #28,296 of 35,345 by trust here, #34,213 by citations
• Computer Vision and Pattern Recognition — 6 citations into it
• Model Architectures — 6 citations into it

Whom Hiromi Nakagawa trusts overall

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

1. Diederik P. Kingma
2. Ronald J. Williams
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Jimmy Ba
6. Alex Krizhevsky
7. Chris J. Maddison
8. Djork-Arné Clevert
9. Peter W. Battaglia
10. Sepp Hochreiter

Who trusts Hiromi Nakagawa overall

1. Ghodai M. Abdelrahman
2. Qing Wang

Papers from Hiromi Nakagawa's perspective

Ordered by how strongly the researchers Hiromi Nakagawa 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Graph-based knowledge tracing: Modeling student proficiency using graph neural networks (2019) — 476 citations