Yuan-Jui Chen

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 3 papers; trusts 30 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it; #23,676 of 35,345 by trust here, #20,836 by citations
• Speech & Audio — 41 citations into it
• Signal Processing — 35 citations into it
• Model Architectures — 10 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Yuan-Jui Chen trusts overall

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

1. Yoshua Bengio
2. Alex Graves
3. Mirjam Wester
4. Daniel W. Griffin
5. Geoffrey E. Hinton
6. Yuxuan Wang
7. Diederik P. Kingma
8. Christophe Veaux
9. Vassil Panayotov
10. Alex Krizhevsky

Who trusts Yuan-Jui Chen overall

1. Xu Tan
2. Mutian He
3. Kurniawati Azizah
4. Tao Qin

Papers from Yuan-Jui Chen's perspective

Ordered by how strongly the researchers Yuan-Jui Chen trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• LM-VC: Zero-Shot Voice Conversion via Speech Generation Based on Language Models (2023) — 47 citations
• Semi-supervised Learning for Multi-speaker Text-to-speech Synthesis Using Discrete Speech Representation (2020) — 8 citations
• End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning (2019) — 100 citations