Yi-Chen Chen

Artificial Intelligence · with Lee · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 181 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 146 citations into it
• Signal Processing — 82 citations into it
• Speech & Audio — 75 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it
• Representation & Self-Supervised Learning — 37 citations into it
• Natural Language Processing — 32 citations into it
• Model Architectures — 19 citations into it
• Evaluation & Benchmarks — 15 citations into it

Whom Yi-Chen Chen trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Ilya Sutskever
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Kaiming He
7. Alex Graves
8. Yann LeCun
9. Oriol Vinyals
10. Tomas Mikolov

Who trusts Yi-Chen Chen overall

1. Kuan-Yu Chen
2. Chengyi Wang
3. Yunfei Chu
4. Luis Villaseñor Pineda
5. Luchen Liu
6. Junyi Ao

Papers from Yi-Chen Chen's perspective

Ordered by how strongly the researchers Yi-Chen 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Order-Free RNN with Visual Attention for Multi-Label Classification (2017) — 159 citations
• Audio Word2vec: Sequence-to-Sequence Autoencoding for Unsupervised Learning of Audio Segmentation and Representation (2019) — 38 citations
• SpeechNet: A Universal Modularized Model for Speech Processing Tasks (2021) — 19 citations
• Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech (2021) — 77 citations
• Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data (2018) — 17 citations