Vadim O. Sokolov

Building and Construction · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 26 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Building and Construction — 13 citations into it; #1,099 of 2,909 by trust here, #1,369 by citations
• Control and Systems Engineering — 12 citations into it; #4,193 of 8,257 by trust here, #3,145 by citations
• Transportation — 12 citations into it
• Artificial Intelligence — 10 citations into it; #19,139 of 35,345 by trust here, #34,943 by citations
• Computational Mechanics — 7 citations into it
• Statistics and Probability — 6 citations into it
• Model Architectures — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Vadim O. Sokolov trusts overall

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

1. Geoffrey E. Hinton
2. Naomi Altman
3. Leo Breiman
4. Yoshua Bengio
5. Robert Tibshirani
6. Li Deng
7. Simon Osindero
8. Yann LeCun
9. Jerome H. Friedman
10. Edward I. George

Who trusts Vadim O. Sokolov overall

1. A. Ozbayoglu
2. Cathy Wu
3. M. Ugur Gudelek
4. Omer Berat Sezer
5. Shengna Guo

Papers from Vadim O. Sokolov's perspective

Ordered by how strongly the researchers Vadim O. Sokolov 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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

• Discussion of ‘Deep learning for finance: deep portfolios’ (2017) — 10 citations
• Deep learning for short-term traffic flow prediction (2016) — 960 citations