Samuel Kiegeland

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 35 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #24,359 of 35,345 by trust here, #30,347 by citations
• Natural Language Processing — 17 citations into it; #4,075 of 5,688 by trust here, #5,214 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #15,093 of 21,575 by trust here, #19,310 by citations
• Reinforcement Learning — 7 citations into it; #1,671 of 2,242 by trust here, #2,092 by citations

Whom Samuel Kiegeland trusts overall

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

1. Matt Post
2. Artem Sokolov
3. Julia Kreutzer
4. Marc'Aurelio Ranzato
5. Ronald J. Williams
6. Ashish Vaswani
7. Khanh Nguyen
8. Adams Wei Yu
9. Geoffrey E. Hinton
10. Yoshua Bengio

Who trusts Samuel Kiegeland overall

1. G. Qian
2. Tianyu Wu
3. Rajkumar Ramamurthy
4. Yann Dubois
5. Wanqiao Xu
6. Shizhu He
7. Prithviraj Ammanabrolu
8. Xuechen Li
9. P. Dupenloup

Papers from Samuel Kiegeland's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation (2021) — 51 citations