Tetsuji Ogawa

Artificial Intelligence · 2003–2018

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Speech & Audio — 11 citations into it
• Signal Processing — 10 citations into it
• Model Architectures — 5 citations into it

Whom Tetsuji Ogawa trusts overall

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

1. Yusuke Shinohara
2. Sergey Ioffe
3. Sepp Hochreiter
4. Seiya Tokui

Papers from Tetsuji Ogawa's perspective

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

1. Long Short-Term Memory
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. ImageNet classification with deep convolutional neural networks
4. Explaining and Harnessing Adversarial Examples
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Domain-Adversarial Training of Neural Networks
9. A Nonparametric Bayesian Approach to Acoustic Model Discovery
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Speaker Invariant Feature Extraction for Zero-Resource Languages with Adversarial Learning (2018) — 32 citations
• I: METHODOLOGY (2003) — 155 citations