Tomoyuki Obuchi

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #29,111 of 35,345 by trust here, #31,361 by citations
• Graph Learning — 12 citations into it
• Statistical and Nonlinear Physics — 11 citations into it; #7,963 of 10,127 by trust here, #8,564 by citations
• Model Architectures — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Tomoyuki Obuchi trusts overall

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

1. Diederik P. Kingma
2. Laurent Massoulié
3. Kaiming He
4. Geoffrey E. Hinton
5. Thomas Kipf
6. Jimmy Ba
7. William L. Hamilton
8. Max Welling
9. David Arthur
10. Yoshua Bengio

Who trusts Tomoyuki Obuchi overall

1. Hoang NT

Papers from Tomoyuki Obuchi's perspective

Ordered by how strongly the researchers Tomoyuki Obuchi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Mean-field theory of graph neural networks in graph partitioning (2018) — 61 citations