James Mullenbach

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #29,899 of 35,345 by trust here, #21,878 by citations
• Natural Language Processing — 13 citations into it

Whom James Mullenbach trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Yoshua Bengio
3. Yoon Kim
4. Geoffrey E. Hinton
5. Tomas Mikolov
6. Dzmitry Bahdanau
7. Jasper Snoek
8. Jimmy Ba
9. Ilya Sutskever
10. Alex Krizhevsky

Who trusts James Mullenbach overall

1. Ilias Chalkidis
2. Cao Xiao
3. Dallas Card
4. Xiang Dai
5. Aurelia Bustos
6. Marina Danilevsky
7. Ion Androutsopoulos
8. Guoyin Wang
9. Edward Choi
10. Michael J.Q. Zhang

Papers from James Mullenbach's perspective

Ordered by how strongly the researchers James Mullenbach trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Explainable Prediction of Medical Codes from Clinical Text (2018) — 692 citations