Nelson Nauata

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 265 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 62 citations into it
• Artificial Intelligence — 32 citations into it
• Graph Learning — 11 citations into it
• Model Architectures — 10 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Nelson Nauata trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. Karen Simonyan
6. Alex Graves
7. Yoshua Bengio
8. Ilya Sutskever
9. Yann LeCun
10. Christian Szegedy

Papers from Nelson Nauata's perspective

Ordered by how strongly the researchers Nelson Nauata 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. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction (2019) — 68 citations
• House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation (2020) — 298 citations
• Structured Label Inference for Visual Understanding (2018) — 23 citations