Paulo da Costa

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Control and Systems Engineering — 17 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Mechanical Engineering — 10 citations into it

Whom Paulo da Costa trusts overall

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

1. Diederik P. Kingma
2. Paul J. Werbos
3. Xiang Li
4. Geoffrey E. Hinton
5. Sepp Hochreiter
6. Yoshua Bengio
7. Alex Krizhevsky
8. Individualized Treat
9. Jimmy Ba
10. J. Urgen Schmidhuber

Who trusts Paulo da Costa overall

1. Manuel Arias Chao
2. Chetan S. Kulkarni

Papers from Paulo da Costa's perspective

Ordered by how strongly the researchers Paulo da Costa 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Remaining Useful Lifetime Prediction via Deep Domain Adaptation (2019) — 346 citations