Koh Takeuchi
Artificial Intelligence · 2018
A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 51 citations into it
- Computer Vision and Pattern Recognition — 34 citations into it
- Probabilistic & Bayesian Methods — 18 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Efficiency & Compression — 12 citations into it
- Optimization & Training — 12 citations into it
- Safety, Robustness & Interpretability — 12 citations into it
- Signal Processing — 10 citations into it
Whom Koh Takeuchi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Jimmy Ba
- Ian J. Goodfellow
- Yann LeCun
- Yoshua Bengio
- Zoubin Ghahramani
- Alex Krizhevsky
- R. Caruana
- Christian Szegedy
Who trusts Koh Takeuchi overall
Papers from Koh Takeuchi's perspective
Ordered by how strongly the researchers Koh Takeuchi trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Few-shot learning of neural networks from scratch by pseudo example optimization (2018) — 55 citations
- Imitation networks: Few-shot learning of neural networks from scratch (2018) — 6 citations