Lidia S. Chao
Artificial Intelligence · 2014–2019
A researcher in the Science corpus: 7 papers; trusts 75 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 95 citations into it; #26,882 of 35,345 by trust here, #8,283 by citations
- Natural Language Processing — 88 citations into it; #4,229 of 5,688 by trust here, #2,132 by citations
- Computer Vision and Pattern Recognition — 44 citations into it
- Model Architectures — 32 citations into it
- Optimization & Training — 14 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Large Language Models — 8 citations into it
Whom Lidia S. Chao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Philipp Koehn
- Franz Joseph Och
- Diederik P. Kingma
- Jörg Tiedemann
- Rico Sennrich
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Ashish Vaswani
- Jimmy Ba
Who trusts Lidia S. Chao overall
Papers from Lidia S. Chao's perspective
Ordered by how strongly the researchers Lidia S. Chao trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- 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)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- Learning Deep Transformer Models for Machine Translation (2019) — 775 citations
- Convolutional Self-Attention Networks (2019) — 135 citations
- Convolutional Self-Attention Network (2018) — 11 citations
- UM-pAligner: Neural Network-Based Parallel Sentence Identification Model (2018) — 11 citations
- Combining Domain Adaptation Approaches for Medical Text Translation (2014) — 9 citations
- UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation (2014) — 135 citations
- Domain Adaptation for Medical Text Translation using Web Resources (2014) — 8 citations