Raj Dabre

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 9 papers; trusts 507 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 212 citations into it; #5,328 of 35,345 by trust here, #9,870 by citations
• Natural Language Processing — 204 citations into it; #1,392 of 5,688 by trust here, #2,634 by citations
• Computer Vision and Pattern Recognition — 119 citations into it; #5,001 of 21,575 by trust here, #8,831 by citations
• Evaluation & Benchmarks — 40 citations into it
• Model Architectures — 28 citations into it
• Machine Translation — 23 citations into it
• Efficiency & Compression — 14 citations into it
• Representation & Self-Supervised Learning — 11 citations into it

Whom Raj Dabre trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rico Sennrich
2. Philipp Koehn
3. Yoshua Bengio
4. Kyunghyun Cho
5. Ilya Sutskever
6. Geoffrey E. Hinton
7. Barret Zoph
8. Dzmitry Bahdanau
9. Diederik P. Kingma
10. Barry Haddow

Who trusts Raj Dabre overall

1. Chenhui Chu
2. Junyi Li
3. Shuhao Gu
4. Bram Bulté
5. Surangika Ranathunga
6. Anoop Kunchukuttan
7. Atsushi Fujita
8. Marlies van der Wees
9. David Vilar
10. Shun Zhang

Papers from Raj Dabre's perspective

Ordered by how strongly the researchers Raj Dabre trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Softmax Tempering for Training Neural Machine Translation Models (2020) — 13 citations
• An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation (2017) — 63 citations
• An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation (2017) — 240 citations
• Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation (2019) — 63 citations
• Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages (2017) — 33 citations
• MMCR4NLP: Multilingual Multiway Corpora Repository for Natural Language Processing (2017) — 14 citations
• Balancing Cost and Benefit with Tied-Multi Transformers (2020) — 7 citations
• A Survey of Multilingual Neural Machine Translation (2019) — 361 citations
• NICT’s Supervised Neural Machine Translation Systems for the WMT19 News Translation Task (2019) — 16 citations