Vicente Iván Sánchez Carmona

Artificial Intelligence · 2015–2018

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #20,982 of 35,345 by trust here, #27,551 by citations
• Natural Language Processing — 13 citations into it; #3,576 of 5,688 by trust here, #4,879 by citations
• Safety, Robustness & Interpretability — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Vicente Iván Sánchez Carmona trusts overall

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

1. Miroslav Kubat
2. Sebastian Thrun
3. Matthew Richardson
4. Mark W. Craven
5. Pierre Isabelle
6. Ankur P. Parikh
7. Sebastian Riedel
8. Qian Chen
9. Brian Milch
10. Bill MacCartney

Who trusts Vicente Iván Sánchez Carmona overall

1. Yonatan Belinkov
2. Yixin Nie
3. Georgina Peake
4. Oana-Maria Camburu
5. Marco Tulio Ribeiro
6. James R. Glass
7. Chris Russell
8. Jun Wang
9. Yicheng Wang
10. Mohit Bansal

Papers from Vicente Iván Sánchez Carmona's perspective

Ordered by how strongly the researchers Vicente Iván Sánchez Carmona trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• Behavior Analysis of NLI Models: Uncovering the Influence of Three Factors on Robustness (2018) — 45 citations
• Towards Extracting Faithful and Descriptive Representations of Latent Variable Models (2015) — 40 citations