Po-Han Chi
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 6 papers; trusts 67 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 129 citations into it; #14,218 of 35,345 by trust here, #7,797 by citations
- Signal Processing — 62 citations into it; #2,878 of 7,572 by trust here, #1,560 by citations
- Speech & Audio — 57 citations into it; #534 of 1,076 by trust here, #371 by citations
- Natural Language Processing — 53 citations into it
- Representation & Self-Supervised Learning — 40 citations into it
- Computer Vision and Pattern Recognition — 32 citations into it
- Large Language Models — 21 citations into it
- Evaluation & Benchmarks — 13 citations into it
Whom Po-Han Chi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Alex Graves
- Jimmy Ba
- Yann LeCun
- Ruslan Salakhutdinov
Who trusts Po-Han Chi overall
- Andy T. Liu
- Yu-An Chung
- Deokjin Seo
- Dongwei Jiang
- Hung-yi Lee
- Puyuan Peng
- Lasse Borgholt
- Shang-Wen Li
- Wei-Ning Hsu
- Abdel-rahman Mohamed
Papers from Po-Han Chi's perspective
Ordered by how strongly the researchers Po-Han Chi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders (2019) — 403 citations
- SUPERB: Speech processing Universal PERformance Benchmark (2021) — 1,225 citations
- Audio Albert: A Lite Bert for Self-Supervised Learning of Audio Representation (2020) — 166 citations
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations
- SpeechNet: A Universal Modularized Model for Speech Processing Tasks (2021) — 19 citations
- Further Boosting BERT-based Models by Duplicating Existing Layers: Some Intriguing Phenomena inside BERT (2020) — 5 citations