Iñigo Lopez-Gazpio
Natural Language Processing · 2015–2018
A researcher in the Science corpus: 3 papers; trusts 41 researchers and is trusted by 57 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 102 citations into it; #1,067 of 5,688 by trust here, #622 by citations
- Artificial Intelligence — 84 citations into it; #4,035 of 35,345 by trust here, #2,620 by citations
- Representation & Self-Supervised Learning — 36 citations into it
- Evaluation & Benchmarks — 25 citations into it; #592 of 3,147 by trust here, #373 by citations
- Computer Vision and Pattern Recognition — 17 citations into it
- Computational Linguistics & Semantics — 9 citations into it
- Molecular Biology — 8 citations into it; #1,752 of 17,773 by trust here, #1,986 by citations
- Information Retrieval & Search — 7 citations into it
Whom Iñigo Lopez-Gazpio trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Geoffrey E. Hinton
- Christopher D. Manning
- Yoshua Bengio
- Jeffrey Pennington
- Ilya Sutskever
- Richard Socher
- Peter D. Turney
- Hinrich Schütze
- Diederik P. Kingma
Who trusts Iñigo Lopez-Gazpio overall
- John Wieting
- Nils Reimers
- Kawin Ethayarajh
- Bowen Zhang
- Tianyu Gao
- Jimmy J. Lin
- Niklas Muennighoff
- Iryna Gurevych
- Timo Schick
- Hinrich Schütze
Papers from Iñigo Lopez-Gazpio's perspective
Ordered by how strongly the researchers Iñigo Lopez-Gazpio trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- GloVe: Global Vectors for Word Representation
Their papers
- SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation (2017) — 2,135 citations
- SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability (2015) — 650 citations
- Uncovering Divergent Linguistic Information in Word Embeddings with Lessons for Intrinsic and Extrinsic Evaluation (2018) — 42 citations