Pavlos Vougiouklis
Artificial Intelligence · 2017–2022
A researcher in the Science corpus: 3 papers; trusts 60 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 68 citations into it; #27,535 of 35,345 by trust here, #9,870 by citations
- Natural Language Processing — 64 citations into it; #4,775 of 5,688 by trust here, #2,307 by citations
- Computer Vision and Pattern Recognition — 22 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Model Architectures — 9 citations into it
- Communication — 7 citations into it
Whom Pavlos Vougiouklis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Oriol Vinyals
- Ilya Sutskever
- Geoffrey E. Hinton
- Yoshua Bengio
- Sepp Hochreiter
- Tomas Mikolov
- Diederik P. Kingma
- Kyunghyun Cho
- Quoc V. Le
- Alex Krizhevsky
Who trusts Pavlos Vougiouklis overall
- Nina Poerner
- Bayu Distiawan Trisedya
- Hinrich Schütze
- Leonardo F. R. Ribeiro
- Nora Kassner
- Zexuan Zhong
- Fabio Petroni
- Guanghui Qin
- Jinhyuk Lee
- Oshin Agarwal
Papers from Pavlos Vougiouklis's perspective
Ordered by how strongly the researchers Pavlos Vougiouklis 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- T-REx: A Large Scale Alignment of Natural Language with Knowledge Base Triples (2018) — 381 citations
- Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples (2017) — 70 citations
- Using natural language generation to bootstrap missing Wikipedia articles: A human-centric perspective (2022) — 13 citations