Yusuke Fujita
Artificial Intelligence · with Watanabe · 2018–2021
A researcher in the Science corpus: 8 papers; trusts 99 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 140 citations into it; #13,783 of 35,345 by trust here, #13,962 by citations
- Signal Processing — 133 citations into it; #2,631 of 7,572 by trust here, #2,114 by citations
- Speech & Audio — 102 citations into it; #741 of 1,076 by trust here, #832 by citations
- Natural Language Processing — 26 citations into it; #3,516 of 5,688 by trust here, #4,449 by citations
- Model Architectures — 23 citations into it
- Evaluation & Benchmarks — 21 citations into it
- Optimization & Training — 11 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
Whom Yusuke Fujita trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel Povey
- Dong Yu
- Diederik P. Kingma
- David Snyder
- Geoffrey E. Hinton
- Ilya Sutskever
- Tom Ko
- Yoshua Bengio
- Jimmy Ba
- Vijayaditya Peddinti
Who trusts Yusuke Fujita overall
- Shota Horiguchi
- Shinji Watanabe
- Naoyuki Kanda
- Tae Jin Park
- Hervé Bredin
- Yawen Xue
- Keisuke Kinoshita
- Leibny Paola García-Perera
- Sanyuan Chen
- Antoine Laurent
Papers from Yusuke Fujita's perspective
Ordered by how strongly the researchers Yusuke Fujita trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
Their papers
- End-to-End Neural Speaker Diarization with Permutation-Free Objectives (2019) — 312 citations
- Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals (2020) — 27 citations
- Encoder-Decoder Based Attractor Calculation for End-to-End Neural Diarization (2021) — 6 citations
- Neural Speaker Diarization with Speaker-Wise Chain Rule (2020) — 51 citations
- End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors (2020) — 230 citations
- Acoustic Modeling for Distant Multi-talker Speech Recognition with Single- and Multi-channel Branches (2019) — 45 citations
- Acoustic Modeling for Overlapping Speech Recognition: Jhu Chime-5 Challenge System (2019) — 21 citations
- Lattice-free State-level Minimum Bayes Risk Training of Acoustic Models (2018) — 29 citations