Alexey Romanov
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 6 papers; trusts 187 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 96 citations into it; #11,484 of 35,345 by trust here, #4,627 by citations
- Natural Language Processing — 69 citations into it
- Computer Vision and Pattern Recognition — 32 citations into it
- Evaluation & Benchmarks — 21 citations into it
- Representation & Self-Supervised Learning — 21 citations into it
- Model Architectures — 16 citations into it
- Molecular Biology — 9 citations into it; #6,665 of 17,773 by trust here, #15,203 by citations
Whom Alexey Romanov trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Oriol Vinyals
- Kyunghyun Cho
- Alex Krizhevsky
- Dzmitry Bahdanau
- Richard Socher
- Jimmy Ba
Who trusts Alexey Romanov overall
- Yifan Peng
- Yasuhide Miura
- Hicham El Boukkouri
- Di Jin
- Peter J. Liu
- Shauli Ravfogel
- Anna Rogers
- Olga Kovaleva
- Jesse Vig
- Yen-Chun Chen
Papers from Alexey Romanov's perspective
Ordered by how strongly the researchers Alexey Romanov 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
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Revealing the Dark Secrets of BERT (2019) — 635 citations
- Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting (2019) — 587 citations
- What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes (2019) — 86 citations
- Adversarial Decomposition of Text Representation (2018) — 47 citations
- Lessons from Natural Language Inference in the Clinical Domain (2018) — 329 citations
- IOTA (Integrable Optics Test Accelerator): facility and experimental beam physics program (2016) — 137 citations