Avraam Tsantekidis

Artificial Intelligence · 2017

A researcher in the Science corpus: 3 papers; trusts 46 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Model Architectures — 15 citations into it
• Management Science and Operations Research — 11 citations into it; #5,597 of 11,946 by trust here, #6,314 by citations
• Optimization & Training — 9 citations into it
• Finance — 8 citations into it; #7,022 of 10,518 by trust here, #8,598 by citations

Whom Avraam Tsantekidis trusts overall

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

1. Diederik P. Kingma
2. Alec N. Kercheval
3. Paul J. Werbos
4. Andrew L. Maas
5. Yoshua Bengio
6. Yann LeCun
7. L. Takeuchi
8. Geoffrey E. Hinton
9. Jimmy Ba
10. Alex Graves

Who trusts Avraam Tsantekidis overall

1. Weiwei Jiang
2. A. Ozbayoglu
3. Omer Berat Sezer
4. M. Ugur Gudelek
5. Dat Thanh Tran
6. Martin Magris
7. Juho Kanniainen
8. Moncef Gabbouj

Papers from Avraam Tsantekidis's perspective

Ordered by how strongly the researchers Avraam Tsantekidis 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. Long Short-Term Memory
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. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Using deep learning to detect price change indications in financial markets (2017) — 145 citations
• Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks (2017) — 329 citations
• Time-series classification using neural Bag-of-Features (2017) — 39 citations