Eder Santana
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 3 papers; trusts 56 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 36 citations into it; #29,881 of 35,345 by trust here, #16,771 by citations
- Computer Vision and Pattern Recognition — 33 citations into it; #8,724 of 21,575 by trust here, #11,721 by citations
- Reinforcement Learning — 23 citations into it
- Automotive Engineering — 13 citations into it; #2,232 of 3,081 by trust here, #1,569 by citations
- Robotics & Control — 11 citations into it
- Control and Systems Engineering — 10 citations into it
- Generative Models — 9 citations into it
- Aerospace Engineering — 8 citations into it
Whom Eder Santana trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- J. Urgen Schmidhuber
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Jimmy Ba
- Alec Radford
- Kaiming He
- Ilya Sutskever
Who trusts Eder Santana overall
- Xiaodan Liang
- Luona Yang
- Jonathan Binas
- Yiping Chen
- Eric P. Xing
- Sergey I. Nikolenko
- Asier Mujika
- Kashyap Chitta
- Tairui Wang
- Daniel Neil
Papers from Eder Santana's perspective
Ordered by how strongly the researchers Eder Santana trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Learning a Driving Simulator (2016) — 232 citations
- Exploring the Limitations of Behavior Cloning for Autonomous Driving (2019) — 703 citations
- A Commute in Data: The comma2k19 Dataset (2018) — 95 citations