Seijin Kobayashi

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 168 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 166 citations into it
• Computer Vision and Pattern Recognition — 103 citations into it
• Optimization & Training — 62 citations into it
• Meta & Continual Learning — 46 citations into it
• Probabilistic & Bayesian Methods — 34 citations into it
• Representation & Self-Supervised Learning — 26 citations into it
• Model Architectures — 24 citations into it
• Reinforcement Learning — 8 citations into it

Whom Seijin Kobayashi trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. L. Eon Bottou
9. Sepp Hochreiter
10. Ilya Sutskever

Papers from Seijin Kobayashi's perspective

Ordered by how strongly the researchers Seijin Kobayashi 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. 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. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Learning where to learn: Gradient sparsity in meta and continual learning (2021) — 60 citations
• Posterior Meta-Replay for Continual Learning (2021) — 76 citations
• Neural networks with late-phase weights (2020) — 40 citations