Kazuhito Takenaka

2017

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

Whom Kazuhito Takenaka trusts overall

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

1. Paul Smolensky

Papers from Kazuhito Takenaka's perspective

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

1. Learning Deep Architectures for AI
2. Learning representations by back-propagating errors
3. Information processing in dynamical systems: foundations of harmony theory
4. Independent component analysis: algorithms and applications
5. Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction
6. Principal Component Analysis
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. ImageNet classification with deep convolutional neural networks
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Gradient-based learning applied to document recognition

Their papers

• Visualization of Driving Behavior Based on Hidden Feature Extraction by Using Deep Learning (2017) — 125 citations