Gemma Boleda
Artificial Intelligence · 2004–2016
A researcher in the Science corpus: 7 papers; trusts 269 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 82 citations into it; #19,577 of 35,345 by trust here, #5,638 by citations
- Natural Language Processing — 75 citations into it; #1,524 of 5,688 by trust here, #2,106 by citations
- Computer Vision and Pattern Recognition — 38 citations into it
- Representation & Self-Supervised Learning — 28 citations into it; #1,011 of 3,145 by trust here, #1,395 by citations
- Model Architectures — 22 citations into it
- Computational Linguistics & Semantics — 12 citations into it
- Multimodal Learning — 10 citations into it
- Information Systems — 5 citations into it
Whom Gemma Boleda trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Marco Baroni
- Tomas Mikolov
- David G. Lowe
- Geoffrey E. Hinton
- Yoshua Bengio
- T. Landauer
- Richard Socher
- Richard Montague
- Alex Krizhevsky
- Ilya Sutskever
Who trusts Gemma Boleda overall
- Yonatan Belinkov
- Aurélie Herbelot
- Alexandre Salle
- Edward Grefenstette
- Manaal Faruqui
- Yu-An Chung
- Douwe Kiela
- Omer Levy
- Zhijian Ou
- Wes Gurnee
Papers from Gemma Boleda's perspective
Ordered by how strongly the researchers Gemma Boleda trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- The LAMBADA dataset: Word prediction requiring a broad discourse context (2016) — 1,160 citations
- Convolutional Neural Network Language Models (2016) — 40 citations
- “Look, some Green Circles!”: Learning to Quantify from Images (2016) — 18 citations
- Formal Distributional Semantics: Introduction to the Special Issue (2016) — 45 citations
- Distributional vectors encode referential attributes (2015) — 98 citations
- Distributional Semantics in Technicolor (2012) — 387 citations
- Relational adjectives as properties of kinds (2004) — 168 citations