Zeyu Jin
Computer Vision and Pattern Recognition · 2018–2021
A researcher in the Science corpus: 5 papers; trusts 34 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 45 citations into it
- Artificial Intelligence — 36 citations into it; #12,987 of 35,345 by trust here, #13,163 by citations
- Signal Processing — 35 citations into it; #3,022 of 7,572 by trust here, #1,241 by citations
- Speech & Audio — 20 citations into it
- Natural Language Processing — 19 citations into it; #2,818 of 5,688 by trust here, #3,107 by citations
Whom Zeyu Jin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Aäron van den Oord
- P. Loizou
- Jimmy Ba
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Graves
- Oriol Vinyals
- Akira Tamamori
- Alex Krizhevsky
Who trusts Zeyu Jin overall
- Jean-Marc Valin
- Takuma Okamoto
- Jan Skoglund
- Max Morrison
- Zhaoxi Mu
- Jaime Lorenzo-Trueba
- Vadim Popov
- Xu Tan
- Po-Chun Hsu
- Xin Eric Wang
Papers from Zeyu Jin's perspective
Ordered by how strongly the researchers Zeyu Jin 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
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Text-based editing of talking-head video (2019) — 291 citations
- Controllable Neural Prosody Synthesis (2020) — 24 citations
- Fftnet: A Real-Time Speaker-Dependent Neural Vocoder (2018) — 107 citations
- Context-Aware Prosody Correction for Text-Based Speech Editing (2021) — 36 citations
- Segmented DAPS (Device and Produced Speech) Dataset (2021)