Eduardo C. Garrido-Merchán

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 3 papers; trusts 95 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it; #24,191 of 35,345 by trust here, #29,412 by citations
• Computer Vision and Pattern Recognition — 19 citations into it
• Natural Language Processing — 13 citations into it
• Computational Theory and Mathematics — 9 citations into it; #8,231 of 12,182 by trust here, #8,756 by citations
• Large Language Models — 9 citations into it
• Optimization & Training — 8 citations into it
• Information Systems — 7 citations into it
• Generative Models — 6 citations into it

Whom Eduardo C. Garrido-Merchán trusts overall

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

1. Yann LeCun
2. Jerome H. Friedman
3. Geoffrey E. Hinton
4. Jasper Snoek
5. Yoshua Bengio
6. Kaiming He
7. James Bergstra
8. Alex Krizhevsky
9. Diederik P. Kingma
10. Carl E. Rasmussen

Who trusts Eduardo C. Garrido-Merchán overall

1. Xilu Wang
2. Yaochu Jin
3. Sebastian Schmitt

Papers from Eduardo C. Garrido-Merchán's perspective

Ordered by how strongly the researchers Eduardo C. Garrido-Merchán 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes (2017) — 289 citations
• ChatGPT is not all you need. A State of the Art Review of large Generative AI models (2023) — 357 citations
• Comparing BERT against traditional machine learning text classification (2020) — 313 citations