Takuya Ohwa

Graph Learning · 2018

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

Subfields

• Graph Learning — 8 citations into it

Whom Takuya Ohwa trusts overall

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

1. Karsten M. Borgwardt
2. Nino Shervashidze
3. Sergey Ioffe

Papers from Takuya Ohwa's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. Dropout: a simple way to prevent neural networks from overfitting
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Human-level concept learning through probabilistic program induction
8. Deep Sparse Rectifier Neural Networks
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Learning Multi-Way Relations via Tensor Decomposition With Neural Networks (2018) — 27 citations