Aarne Talman

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 67 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #25,284 of 35,345 by trust here, #33,294 by citations
• Natural Language Processing — 36 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it; #15,535 of 21,575 by trust here, #20,756 by citations
• Evaluation & Benchmarks — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Aarne Talman trusts overall

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

1. Diederik P. Kingma
2. Jeffrey Pennington
3. Jacob Devlin
4. Richard Socher
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Jimmy Ba
8. Qian Chen
9. Christopher D. Manning
10. Rico Sennrich

Who trusts Aarne Talman overall

1. Xiang Zhou
2. Mohit Bansal
3. Yang Zhang
4. Loïc Barrault
5. Liqun Deng

Papers from Aarne Talman's perspective

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

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

Their papers

• Testing the Generalization Power of Neural Network Models across NLI Benchmarks (2018) — 55 citations
• The University of Helsinki Submissions to the WMT19 News Translation Task (2019) — 7 citations
• Predicting Prosodic Prominence from Text with Pre-trained Contextualized Word Representations (2019) — 31 citations