Reginald Long
Natural Language Processing · 2016
A researcher in the Science corpus: 1 paper; trusts 34 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 23 citations into it; #2,318 of 5,688 by trust here, #3,529 by citations
- Artificial Intelligence — 19 citations into it; #12,058 of 35,345 by trust here, #17,412 by citations
- Computer Vision and Pattern Recognition — 8 citations into it
Whom Reginald Long trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Percy Liang
- Luke S. Zettlemoyer
- David L. Chen
- Michael Collins
- Panupong Pasupat
- John C. Duchi
- Raymond J. Mooney
- Yoav Artzi
- Geoffrey E. Hinton
- Yoshua Bengio
Who trusts Reginald Long overall
- Hsin-Yuan Huang
- Wen-tau Yih
- Eunsol Choi
- Zhuang Li
- Siddharth Karamcheti
- Belinda Z. Li
- Rui Zhang
- Kelvin Guu
- Tao Yu
- Bhavana Dalvi
Papers from Reginald Long's perspective
Ordered by how strongly the researchers Reginald Long 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Simpler Context-Dependent Logical Forms via Model Projections (2016) — 106 citations