Ryan Marcus

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Management Science and Operations Research — 10 citations into it
• Reinforcement Learning — 10 citations into it

Whom Ryan Marcus trusts overall

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

1. Jimmy Ba
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Xavier Glorot
6. Alex Krizhevsky
7. Leo Breiman
8. Tomas Mikolov
9. Stefan Schaal
10. Yann LeCun

Papers from Ryan Marcus's perspective

Ordered by how strongly the researchers Ryan Marcus 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. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Bao: Making Learned Query Optimization Practical (2020) — 321 citations
• Neo: A Learned Query Optimizer (2019) — 518 citations