José Cristóbal Riquelme Santos

Artificial Intelligence · 2006–2020

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #21,790 of 35,345 by trust here, #23,731 by citations
• Management Science and Operations Research — 29 citations into it
• Information Systems — 14 citations into it
• Model Architectures — 14 citations into it
• Time-Series & Forecasting — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Economics and Econometrics — 9 citations into it

Whom José Cristóbal Riquelme Santos trusts overall

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

1. Michael I. Jordan
2. G. Zhang
3. Huan Liu
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. J. Urgen Schmidhuber
7. Ha Young Kim
8. Lei Yu
9. Peter Clark
10. Diederik P. Kingma

Who trusts José Cristóbal Riquelme Santos overall

1. Yvan Saeys
2. Lin Sun
3. Juanying Xie

Papers from José Cristóbal Riquelme Santos's perspective

Ordered by how strongly the researchers José Cristóbal Riquelme Santos 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Incremental wrapper-based gene selection from microarray data for cancer classification (2006) — 903 citations
• An Experimental Review on Deep Learning Architectures for Time Series Forecasting (2020) — 451 citations
• Searching for rules to detect defective modules: A subgroup discovery approach (2012) — 63 citations