Christopher Alberti
Artificial Intelligence · 2009–2019
A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 22 citations into it; #15,000 of 35,345 by trust here, #19,873 by citations
- Natural Language Processing — 18 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
Whom Christopher Alberti trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Rico Sennrich
- Hwee Tou Ng
- Noam Shazeer
- Ilya Sutskever
- Daniel Dahlmeier
- Barry Haddow
- Shamil Chollampatt
- Joel R. Tetreault
- Christopher Bryant
- Oriol Vinyals
Who trusts Christopher Alberti overall
- Kishore Prahallad
- Hank Liao
- Norbert Braunschweiler
- Felix Stahlberg
- Heiga Zen
- Roman Grundkiewicz
- Tao Ge
Papers from Christopher Alberti's perspective
Ordered by how strongly the researchers Christopher Alberti trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Their papers
- A factor automaton approach for the forced alignment of long speech recordings (2009) — 50 citations
- Corpora Generation for Grammatical Error Correction (2019) — 146 citations