Steven Layne
Artificial Intelligence · 2019
A researcher in the Science corpus: 1 paper; trusts 54 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 28 citations into it; #27,713 of 35,345 by trust here, #34,943 by citations
- Natural Language Processing — 25 citations into it; #4,569 of 5,688 by trust here, #5,662 by citations
- Computer Vision and Pattern Recognition — 10 citations into it
- Model Architectures — 6 citations into it
- Optimization & Training — 5 citations into it
Whom Steven Layne trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Ilya Sutskever
- Geoffrey E. Hinton
- Sepp Hochreiter
- Yoshua Bengio
- Oriol Vinyals
- Katja Filippova
- Richard Socher
- J. Urgen Schmidhuber
- Alex Krizhevsky
Who trusts Steven Layne overall
Papers from Steven Layne's perspective
Ordered by how strongly the researchers Steven Layne trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- 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)
- Dropout: a simple way to prevent neural networks from overfitting