Tsubasa Ochiai
Signal Processing · 2016–2023
A researcher in the Science corpus: 5 papers; trusts 46 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 74 citations into it; #5,222 of 7,572 by trust here, #1,012 by citations
- Artificial Intelligence — 65 citations into it; #24,970 of 35,345 by trust here, #8,210 by citations
- Speech & Audio — 35 citations into it; #769 of 1,076 by trust here, #386 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Natural Language Processing — 18 citations into it
- Computational Mechanics — 13 citations into it
- Model Architectures — 11 citations into it
- Multimodal Learning — 5 citations into it
Whom Tsubasa Ochiai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Triantafyllos Afouras
- Yoshua Bengio
- R. Caruana
- John R. Hershey
- Dzmitry Bahdanau
- Emmanuel Vincent
- Andrew Zisserman
- Jimmy Ba
Who trusts Tsubasa Ochiai overall
Papers from Tsubasa Ochiai's perspective
Ordered by how strongly the researchers Tsubasa Ochiai trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- ESPnet: End-to-End Speech Processing Toolkit (2018) — 1,730 citations
- SpeakerBeam: Speaker Aware Neural Network for Target Speaker Extraction in Speech Mixtures (2019) — 288 citations
- Neural Target Speech Extraction: An overview (2023) — 166 citations
- Multimodal SpeakerBeam: Single Channel Target Speech Extraction with Audio-Visual Speaker Clues (2019) — 70 citations
- Automatic node selection for Deep Neural Networks using Group Lasso regularization (2016) — 25 citations