Mario Linares Vásquez

Information Systems · 2015

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 33 citations into it; #2,545 of 8,771 by trust here, #2,406 by citations
• Artificial Intelligence — 26 citations into it; #13,848 of 35,345 by trust here, #14,718 by citations
• Software — 23 citations into it
• Natural Language Processing — 22 citations into it; #2,573 of 5,688 by trust here, #3,107 by citations
• Model Architectures — 10 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Large Language Models — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Mario Linares Vásquez trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Tomas Mikolov
4. Ilya Sutskever
5. J. Urgen Schmidhuber
6. Yann LeCun
7. Ahmed E. Hassan
8. Andriy Mnih
9. Alex Krizhevsky
10. Jeffrey L. Elman

Who trusts Mario Linares Vásquez overall

1. Vincent J. Hellendoorn
2. Rafael-Michael Karampatsis
3. Xiaodong Gu
4. Charles Sutton
5. Wei Fu

Papers from Mario Linares Vásquez's perspective

Ordered by how strongly the researchers Mario Linares Vásquez 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. Attention is All you Need (Neural Information Processing Systems)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Toward Deep Learning Software Repositories (2015) — 323 citations
• RCLinker: Automated Linking of Issue Reports and Commits Leveraging Rich Contextual Information (2015) — 47 citations