Antonio J. Sánchez-Esguevillas

Artificial Intelligence · 2014–2020

A researcher in the Science corpus: 4 papers; trusts 14 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #19,316 of 35,345 by trust here, #14,718 by citations
• Computer Networks and Communications — 31 citations into it; #4,810 of 9,886 by trust here, #5,518 by citations
• Electrical and Electronic Engineering — 16 citations into it
• Signal Processing — 14 citations into it; #3,978 of 7,572 by trust here, #4,373 by citations
• Computer Vision and Pattern Recognition — 9 citations into it
• Model Architectures — 9 citations into it
• Management Science and Operations Research — 6 citations into it
• Generative Models — 5 citations into it

Whom Antonio J. Sánchez-Esguevillas trusts overall

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

1. Diederik P. Kingma
2. Andrew William Moore
3. Sven Behnke
4. Geoffrey E. Hinton
5. Zachary Chase Lipton
6. Charu C. Aggarwal
7. Max Welling
8. Yoshua Bengio
9. Alex Krizhevsky
10. Yann LeCun

Who trusts Antonio J. Sánchez-Esguevillas overall

1. Iqbal H. Sarker
2. Nivedita Mishra
3. Shahbaz Rezaei

Papers from Antonio J. Sánchez-Esguevillas's perspective

Ordered by how strongly the researchers Antonio J. Sánchez-Esguevillas 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings (2014) — 476 citations
• Application of deep reinforcement learning to intrusion detection for supervised problems (2020) — 298 citations
• Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT (2017) — 267 citations
• Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things (2017) — 578 citations