Vasileios Lampos
Artificial Intelligence · 2010–2020
A researcher in the Science corpus: 5 papers; trusts 27 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 27 citations into it; #32,926 of 35,345 by trust here, #28,481 by citations
- Sociology and Political Science — 14 citations into it
- Natural Language Processing — 12 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Epidemiology — 7 citations into it; #688 of 2,148 by trust here, #1,250 by citations
- Statistics and Probability — 7 citations into it
- Statistical Learning Theory — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Vasileios Lampos trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Francis R. Bach
- Leo Breiman
- Radford M. Neal
- Gerlof J. Bouma
- Andrew Y. Ng
- Michael I. Jordan
- Edward Snelson
- Yuhai Wu
- Jianbo Shi
- Geoffrey E. Hinton
Who trusts Vasileios Lampos overall
- Daniel Preotiuc-Pietro
- John M. Cinnamon
- Daniel Gayo-Avello
- Harald Schoen
- Nadine Schuurman
- Lucie Flekova
- Alessio Signorini
- Nikolaos Aletras
- Ye Liu
- Ilias Chalkidis
Papers from Vasileios Lampos's perspective
Ordered by how strongly the researchers Vasileios Lampos trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- 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)
Their papers
- Studying User Income through Language, Behaviour and Affect in Social Media (2015) — 216 citations
- Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective (2016) — 723 citations
- Digital technologies in the public-health response to COVID-19 (2020) — 917 citations
- Predicting and Characterising User Impact on Twitter (2014) — 83 citations
- Tracking the flu pandemic by monitoring the social web (2010) — 358 citations