Albert Haque

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 4 papers; trusts 496 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 139 citations into it; #16,667 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 106 citations into it; #32,517 of 35,345 by trust here, #15,866 by citations
• Model Architectures — 33 citations into it
• Biomedical Engineering — 22 citations into it; #7,483 of 10,734 by trust here, #8,509 by citations
• Human-Computer Interaction — 17 citations into it
• Optimization & Training — 15 citations into it
• Privacy & Security — 15 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Albert Haque trusts overall

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

1. Geoffrey E. Hinton
2. David G. Lowe
3. Alex Krizhevsky
4. Yann LeCun
5. Yoshua Bengio
6. Diederik P. Kingma
7. Kaiming He
8. Karen Simonyan
9. Ronald J. Williams
10. Ilya Sutskever

Who trusts Albert Haque overall

1. Zelun Luo
2. Katsuyuki Nakamura
3. Nikolaos Karianakis
4. Yansong Tang
5. Gyeongsik Moon
6. Michael Crawshaw
7. Alexandre Alahi
8. Christopher Fifty
9. Boya Peng
10. Serena Yeung

Papers from Albert Haque's perspective

Ordered by how strongly the researchers Albert Haque 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. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Recurrent Attention Models for Depth-Based Person Identification (2016) — 152 citations
• Dynamic Task Prioritization for Multitask Learning (2018) — 457 citations
• Towards Viewpoint Invariant 3D Human Pose Estimation (2016) — 176 citations
• Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference (2018) — 228 citations