Tomás Henrique Maul

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 204 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it
• Model Architectures — 22 citations into it
• Molecular Biology — 10 citations into it
• Cognitive Neuroscience — 8 citations into it
• Natural Language Processing — 8 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Tomás Henrique Maul trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Mark Newman
4. J. Urgen Schmidhuber
5. Sepp Hochreiter
6. Alex Krizhevsky
7. Kaiming He
8. Yann LeCun
9. Duncan J. Watts
10. Ross B. Girshick

Papers from Tomás Henrique Maul's perspective

Ordered by how strongly the researchers Tomás Henrique Maul 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A review of modularization techniques in artificial neural networks (2019) — 93 citations