Amanda D. Smith

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it

Whom Amanda D. Smith trusts overall

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

1. James Bergstra
2. Zachary Chase Lipton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Sepp Hochreiter
6. Geoffrey E. Hinton
7. J. Urgen Schmidhuber
8. Jimmy Ba

Papers from Amanda D. Smith's perspective

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

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

Their papers

• Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks (2018) — 676 citations
• Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies (2018) — 168 citations