Laura Seiffe
Artificial Intelligence · 2017
A researcher in the Science corpus: 2 papers; trusts 69 researchers and is trusted by 54 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #6,725 of 35,345 by trust here, #11,072 by citations
- Natural Language Processing — 32 citations into it; #982 of 5,688 by trust here, #1,966 by citations
- Computer Vision and Pattern Recognition — 15 citations into it; #5,598 of 21,575 by trust here, #7,750 by citations
- Evaluation & Benchmarks — 10 citations into it
- Information Retrieval & Search — 7 citations into it; #300 of 1,022 by trust here, #602 by citations
- Information Systems — 6 citations into it
Whom Laura Seiffe trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Sepp Hochreiter
- Geoffrey E. Hinton
- Danqi Chen
- Yoshua Bengio
- Jimmy Ba
- Richard Socher
- J. Urgen Schmidhuber
- Yarin Gal
- Alex Krizhevsky
Who trusts Laura Seiffe overall
- Minghao Hu
- Christopher Clark
- Dirk Weissenborn
- Johannes Welbl
- Nicola De Cao
- Jianfeng Gao
- Debajyoti Chatterjee
- Yelong Shen
- Leon Weber
- Matt Gardner
Papers from Laura Seiffe's perspective
Ordered by how strongly the researchers Laura Seiffe trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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)
Their papers
- Making Neural QA as Simple as Possible but not Simpler (2017) — 220 citations
- FastQA: A Simple and Efficient Neural Architecture for Question Answering (2017) — 69 citations