Tomasz Dwojak
Artificial Intelligence · 2016–2018
A researcher in the Science corpus: 5 papers; trusts 82 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 79 citations into it; #6,718 of 35,345 by trust here, #7,606 by citations
- Natural Language Processing — 63 citations into it; #2,013 of 5,688 by trust here, #1,966 by citations
- Computer Vision and Pattern Recognition — 30 citations into it; #7,809 of 21,575 by trust here, #7,657 by citations
- Model Architectures — 15 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Tomasz Dwojak trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Rico Sennrich
- Matthew D. Zeiler
- Yoshua Bengio
- Dzmitry Bahdanau
- Kyunghyun Cho
- Tomas Mikolov
- Barry Haddow
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
Who trusts Tomasz Dwojak overall
- Felix Stahlberg
- Marcin Junczys-Dowmunt
- Pierre Isabelle
- Antonio Toral
- Martin Popel
- Heng Yu
- Philipp Koehn
- Chenze Shao
- Alham Fikri Aji
- Roman Grundkiewicz
Papers from Tomasz Dwojak's perspective
Ordered by how strongly the researchers Tomasz Dwojak trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Sequence to Sequence Learning with Neural Networks (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)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Marian: Fast Neural Machine Translation in C++ (2018) — 797 citations
- Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions (2016) — 202 citations
- Predicting Target Language CCG Supertags Improves Neural Machine Translation (2017) — 82 citations
- The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT (2016) — 60 citations
- Syntax-aware Neural Machine Translation Using CCG (2017) — 18 citations