Niels Justesen

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 66 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #30,371 of 35,345 by trust here, #17,110 by citations
• Reinforcement Learning — 36 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Optimization & Training — 8 citations into it
• Cognitive Neuroscience — 7 citations into it
• Sociology and Political Science — 7 citations into it; #20,359 of 22,756 by trust here, #19,300 by citations
• Computational Theory and Mathematics — 6 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Niels Justesen trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. J. Urgen Schmidhuber
6. Volodymyr Mnih
7. Ilya Sutskever
8. Jimmy Ba
9. Alex Graves
10. Yann LeCun

Who trusts Niels Justesen overall

1. Sebastian Risi
2. Rui Wang
3. Karl Cobbe
4. Minqi Jiang
5. Emmanuel Bengio
6. Jeff Clune
7. Yuxi Li
8. Khimya Khetarpal
9. Julian Togelius
10. Joel Lehman

Papers from Niels Justesen's perspective

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

1. ImageNet classification with deep convolutional neural networks
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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation (2018) — 205 citations
• Learning macromanagement in starcraft from replays using deep learning (2017) — 73 citations
• Automated Curriculum Learning by Rewarding Temporally Rare Events (2018) — 20 citations