Pedro J. Gonçalves

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #20,396 of 35,345 by trust here, #24,417 by citations
• Statistics and Probability — 10 citations into it; #7,533 of 12,932 by trust here, #6,853 by citations
• Probabilistic & Bayesian Methods — 8 citations into it; #1,066 of 1,525 by trust here, #1,136 by citations

Whom Pedro J. Gonçalves trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Edward Meeds
4. MARK A. Beaumont
5. Simon N. Wood
6. Michael G. B. Blum
7. Max Welling
8. Yoshua Bengio
9. Peter J. Diggle
10. George Papamakarios

Who trusts Pedro J. Gonçalves overall

1. Joeri Hermans
2. Conor Durkan
3. George Papamakarios
4. Gilles Louppe
5. J. Brehmer
6. Charlie Nash
7. David S. Greenberg
8. Volodimir Begy
9. Rafael Izbicki

Papers from Pedro J. Gonçalves's perspective

Ordered by how strongly the researchers Pedro J. Gonçalves 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. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Flexible statistical inference for mechanistic models of neural dynamics (2017) — 334 citations