Daniyar Turmukhambetov

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 3 papers; trusts 303 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it; #6,736 of 21,575 by trust here, #5,987 by citations
• Artificial Intelligence — 18 citations into it
• Media Technology — 18 citations into it
• Model Architectures — 9 citations into it; #766 of 2,278 by trust here, #894 by citations

Whom Daniyar Turmukhambetov trusts overall

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

1. Ce Liu
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Jitendra Malik
6. Karen Simonyan
7. Yann LeCun
8. Yoshua Bengio
9. Diederik P. Kingma
10. Andrew Zisserman

Who trusts Daniyar Turmukhambetov overall

1. Daniel E. Worrall
2. Jun-Yan Zhu
3. Taco Cohen
4. Risi Kondor
5. David W. Romero
6. Erik J. Bekkers
7. Diego Marcos
8. Taesung Park
9. Max Welling
10. Yi Liao

Papers from Daniyar Turmukhambetov's perspective

Ordered by how strongly the researchers Daniyar Turmukhambetov 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• Harmonic Networks: Deep Translation and Rotation Equivariance (2016) — 783 citations
• Modeling object appearance using Context-Conditioned Component Analysis (2015) — 5 citations
• Self-Supervised Monocular Depth Hints (2019) — 294 citations