Cyril Allauzen
Artificial Intelligence · 2007–2020
A researcher in the Science corpus: 9 papers; trusts 28 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 66 citations into it; #6,708 of 35,345 by trust here, #10,065 by citations
- Natural Language Processing — 40 citations into it
- Speech & Audio — 27 citations into it; #401 of 1,076 by trust here, #869 by citations
- Signal Processing — 19 citations into it; #2,222 of 7,572 by trust here, #5,829 by citations
- Model Architectures — 17 citations into it; #1,787 of 2,278 by trust here, #2,162 by citations
- Computer Vision and Pattern Recognition — 7 citations into it
Whom Cyril Allauzen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mehryar Mohri
- Andreas Stolcke
- Alex Graves
- Michael D. Riley
- Michael Collins
- Geoffrey E. Hinton
- Frederick Jelinek
- Fernando C Pereira
- Yoshua Bengio
- J. Urgen Schmidhuber
Who trusts Cyril Allauzen overall
- Felix Stahlberg
- Danielle Saunders
- Kanishka Rao
- Rohit Prabhavalkar
- Anjuli Kannan
- Petar S. Aleksic
- Jiameng Gao
- John Dines
- Jan Chorowski
- Bill Byrne
Papers from Cyril Allauzen's perspective
Ordered by how strongly the researchers Cyril Allauzen 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Attention is All you Need (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)
- Layer Normalization
- Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
Their papers
- OpenFst: A General and Efficient Weighted Finite-State Transducer Library (2007) — 672 citations
- Bayesian Language Model Interpolation for Mobile Speech Input (2011) — 54 citations
- Encoding linear models as weighted finite-state transducers (2014) — 26 citations
- Composition-based on-the-fly rescoring for salient n-gram biasing (2015) — 76 citations
- Improved recognition of contact names in voice commands (2015) — 50 citations
- Hybrid Autoregressive Transducer (HAT) (2020) — 174 citations
- Federated Learning of N-Gram Language Models (2019) — 80 citations
- Transliterated Mobile Keyboard Input via Weighted Finite-State Transducers (2017) — 31 citations
- The OpenGrm open-source finite-state grammar software libraries (2012) — 120 citations