Gabriel Sepulveda

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 20 citations into it
• Reinforcement Learning — 11 citations into it

Whom Gabriel Sepulveda trusts overall

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

1. Diederik P. Kingma
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Sepp Hochreiter
5. Sergey Ioffe
6. Alex Krizhevsky
7. Dean A. Pomerleau
8. Yoshua Bengio
9. Jimmy Ba
10. J. Urgen Schmidhuber

Papers from Gabriel Sepulveda's perspective

Ordered by how strongly the researchers Gabriel Sepulveda trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Behavioral Approach to Visual Navigation with Graph Localization Networks (2019) — 109 citations