Kristjan Arumae
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 134 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 59 citations into it; #16,012 of 35,345 by trust here, #30,347 by citations
- Natural Language Processing — 52 citations into it; #1,887 of 5,688 by trust here, #4,361 by citations
- Evaluation & Benchmarks — 13 citations into it
- Computer Vision and Pattern Recognition — 12 citations into it
Whom Kristjan Arumae trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Chin-Yew Lin
- Christopher D. Manning
- Geoffrey E. Hinton
- Nitish Srivastava
- Jimmy Ba
- Richard Socher
- Yoshua Bengio
- Jeffrey Pennington
- Mirella Lapata
Who trusts Kristjan Arumae overall
- Ming Zhong
- Joshua Maynez
- Pengfei Liu
- Thomas Scialom
- Mo Yu
- Shashi Narayan
- Rahul Aralikatte
- Danqing Wang
- Fei Liu
- Shiyu Chang
Papers from Kristjan Arumae's perspective
Ordered by how strongly the researchers Kristjan Arumae trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- 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
- 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)
Their papers
- Reinforced Extractive Summarization with Question-Focused Rewards (2018) — 33 citations
- Guiding Extractive Summarization with Question-Answering Rewards (2019) — 35 citations