M. Ugur Gudelek
Management Science and Operations Research · 2017–2020
A researcher in the Science corpus: 3 papers; trusts 302 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Management Science and Operations Research — 259 citations into it; #4,037 of 11,946 by trust here, #4,921 by citations
- Time-Series & Forecasting — 162 citations into it; #110 of 381 by trust here, #147 by citations
- Artificial Intelligence — 150 citations into it; #21,767 of 35,345 by trust here, #22,463 by citations
- Economics & Operations Research — 96 citations into it
- Finance — 95 citations into it; #5,860 of 10,518 by trust here, #9,371 by citations
- Economics and Econometrics — 86 citations into it; #12,752 of 23,481 by trust here, #21,405 by citations
- Electrical and Electronic Engineering — 70 citations into it
- Signal Processing — 48 citations into it
Whom M. Ugur Gudelek trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Omer Berat Sezer
- Alex Krizhevsky
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
- Matthew D. Zeiler
- A. Ozbayoglu
- J. Urgen Schmidhuber
Who trusts M. Ugur Gudelek overall
Papers from M. Ugur Gudelek's perspective
Ordered by how strongly the researchers M. Ugur Gudelek trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A deep learning based stock trading model with 2-D CNN trend detection (2017) — 121 citations
- Deep Learning for Financial Applications : A Survey (2020) — 513 citations
- Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019) — 1,431 citations