Santiago Ontañón

Artificial Intelligence · 2007–2021

A researcher in the Science corpus: 11 papers; trusts 191 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 208 citations into it; #11,293 of 35,345 by trust here, #2,953 by citations
• Natural Language Processing — 113 citations into it; #3,961 of 5,688 by trust here, #2,440 by citations
• Computer Vision and Pattern Recognition — 110 citations into it; #13,938 of 21,575 by trust here, #12,419 by citations
• Model Architectures — 81 citations into it; #1,125 of 2,278 by trust here, #387 by citations
• Large Language Models — 45 citations into it
• Evaluation & Benchmarks — 31 citations into it
• Efficiency & Compression — 25 citations into it
• Reinforcement Learning — 19 citations into it; #2,130 of 2,242 by trust here, #1,253 by citations

Whom Santiago Ontañón trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Ilya Sutskever
5. Ashish Vaswani
6. Alex Krizhevsky
7. Noam Shazeer
8. Yann LeCun
9. Kaiming He
10. Alex Graves

Who trusts Santiago Ontañón overall

1. Gabriel Synnaeve
2. David Churchill
3. Yi Tay
4. Glen Robertson
5. Victor do Nascimento Silva
6. James Lee-Thorp
7. Pierre Bessière
8. Mostafa Dehghani
9. Siming Liu
10. Nantas Nardelli

Papers from Santiago Ontañón's perspective

Ordered by how strongly the researchers Santiago Ontañón trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Big Bird: Transformers for Longer Sequences (2020) — 2,963 citations
• A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft (2013) — 463 citations
• ETC: Encoding Long and Structured Data in Transformers (2020) — 58 citations
• ETC: Encoding Long and Structured Inputs in Transformers (2020) — 415 citations
• FNet: Mixing Tokens with Fourier Transforms (2021) — 751 citations
• Case-Based Planning and Execution for Real-Time Strategy Games (2007) — 173 citations
• Game-Tree Search over High-Level Game States in RTS Games (2014) — 44 citations
• LongT5: Efficient Text-To-Text Transformer for Long Sequences (2021) — 414 citations
• Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss? (2018) — 65 citations
• Policies for Active Learning from Demonstration (2017) — 14 citations
• Multiagent Inductive Learning: an Argumentation-based Approach (2010) — 34 citations