David Nader-Palacio

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Natural Language Processing — 27 citations into it
• Model Architectures — 7 citations into it

Whom David Nader-Palacio trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Chin-Yew Lin

Papers from David Nader-Palacio's perspective

Ordered by how strongly the researchers David Nader-Palacio trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Attention is All you Need (Neural Information Processing Systems)
3. Dropout: a simple way to prevent neural networks from overfitting
4. ImageNet classification with deep convolutional neural networks
5. Layer Normalization
6. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Gradient-based learning applied to document recognition
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks (2021) — 285 citations