Christophe Servan
Artificial Intelligence · 2011–2016
A researcher in the Science corpus: 6 papers; trusts 36 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it; #12,835 of 35,345 by trust here, #9,465 by citations
- Natural Language Processing — 61 citations into it; #4,952 of 5,688 by trust here, #2,846 by citations
- Computer Vision and Pattern Recognition — 19 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Machine Translation — 7 citations into it; #88 of 292 by trust here, #57 by citations
- Large Language Models — 5 citations into it
Whom Christophe Servan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Holger Schwenk
- Franz Joseph Och
- Andreas Stolcke
- Philipp Koehn
- Qin Gao
- Sadaf Abdul Rauf
- Tomas Mikolov
- David Chiang
- Yoshua Bengio
- Stephan Vogel
Who trusts Christophe Servan overall
- Ilya Sutskever
- Changhan Wang
- Oriol Vinyals
- Houda Bouamor
- Quoc V. Le
- Ondrej Bojar
- Ron J. Weiss
- Ye Jia
- A. Abdelsalam
- Mattia Antonino Di Gangi
Papers from Christophe Servan's perspective
Ordered by how strongly the researchers Christophe Servan 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- SYSTRAN's Pure Neural Machine Translation Systems (2016) — 128 citations
- Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation (2016) — 340 citations
- MultiVec: a Multilingual and Multilevel Representation Learning Toolkit for NLP (2016) — 56 citations
- LIUM’s SMT Machine Translation Systems for WMT 2012 (2012) — 16 citations
- LIUM’s SMT Machine Translation Systems for WMT 2011 (2011) — 15 citations
- Investigations on Translation Model Adaptation Using Monolingual Data (2011) — 63 citations