Javier I. González

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 6 papers; trusts 56 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 88 citations into it; #15,798 of 35,345 by trust here, #12,083 by citations
• Optimization & Training — 37 citations into it
• Probabilistic & Bayesian Methods — 22 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Management Science and Operations Research — 18 citations into it; #8,412 of 11,946 by trust here, #7,638 by citations
• Computational Theory and Mathematics — 17 citations into it; #6,789 of 12,182 by trust here, #3,681 by citations
• Privacy & Security — 14 citations into it
• Signal Processing — 14 citations into it

Whom Javier I. González trusts overall

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

1. Jasper Snoek
2. Carl E. Rasmussen
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. James Bergstra
7. Hugo Larochelle
8. Christopher K. I. Williams
9. Yann LeCun
10. Alex Krizhevsky

Who trusts Javier I. González overall

1. Kirthevasan Kandasamy
2. Jeff Schneider
3. Colin White
4. Barnab'as P'oczos
5. Liam Li
6. Vu Nguyen
7. Yimin Huang
8. Akshay Krishnamurthy
9. Jungtaek Kim
10. Daniel E. Ho

Papers from Javier I. González's perspective

Ordered by how strongly the researchers Javier I. González 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. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Batch Bayesian Optimization via Local Penalization (2015) — 413 citations
• Variational Auto-encoded Deep Gaussian Processes (2015) — 138 citations
• Bayesian Optimization for Synthetic Gene Design (2015) — 85 citations
• BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization (2020) — 59 citations
• Automatic Discovery of Privacy–Utility Pareto Fronts (2019) — 32 citations
• Bayesian Optimization with Tree-structured Dependencies (2017) — 58 citations