Keith J. Monaghan

Molecular Biology · 2017

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 14 citations into it
• Artificial Intelligence — 11 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Keith J. Monaghan trusts overall

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

1. Naomi S. Altman
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Andrew McCallum
5. Hugo Larochelle
6. Ramón Díaz-Uriarte
7. Nitish Srivastava
8. Alex Krizhevsky
9. Itamar Arel
10. Pierre Baldi

Who trusts Keith J. Monaghan overall

1. Alexandru Korotcov
2. Hongming Chen

Papers from Keith J. Monaghan's perspective

Ordered by how strongly the researchers Keith J. Monaghan 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Dropout: a simple way to prevent neural networks from overfitting
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data (2017) — 271 citations