Ardi Tampuu

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 98 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it
• Artificial Intelligence — 63 citations into it; #21,747 of 35,345 by trust here, #9,275 by citations
• Reinforcement Learning — 45 citations into it; #1,519 of 2,242 by trust here, #926 by citations
• Automotive Engineering — 44 citations into it
• Model Architectures — 7 citations into it
• Computational Mechanics — 5 citations into it

Whom Ardi Tampuu trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Richard S. Sutton
5. Ronald J. Williams
6. Diederik P. Kingma
7. Yoshua Bengio
8. Ilya Sutskever
9. Yann LeCun
10. Ross B. Girshick

Who trusts Ardi Tampuu overall

1. Tabish Rashid
2. Jakob N. Foerster
3. Alex Peysakhovich
4. Adam Lerer
5. Kyunghwan Son
6. Shariq Iqbal
7. Shimon Whiteson
8. Matthew Veres
9. Gregory Farquhar
10. Mikayel Samvelyan

Papers from Ardi Tampuu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Multiagent cooperation and competition with deep reinforcement learning (2015) — 1,014 citations
• A Survey of End-to-End Driving: Architectures and Training Methods (2020) — 323 citations
• ViraMiner: Deep learning on raw DNA sequences for identifying viral genomes in human samples (2019) — 111 citations