Sima Siami‐Namini

Management Science and Operations Research · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 21 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 19 citations into it; #6,505 of 11,946 by trust here, #7,638 by citations
• Artificial Intelligence — 18 citations into it
• Model Architectures — 12 citations into it
• Finance — 10 citations into it
• Economics and Econometrics — 8 citations into it
• Signal Processing — 6 citations into it; #5,178 of 7,572 by trust here, #6,836 by citations

Whom Sima Siami‐Namini trusts overall

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

1. J. Urgen Schmidhuber
2. Mehdi Khashei
3. Alex Graves
4. Nicolas Huck
5. Sepp Hochreiter
6. M. Pesaran
7. Felix Alexander Gers
8. Mehdi Bijari
9. Thomas G. Fischer
10. Thabani Nyoni

Who trusts Sima Siami‐Namini overall

1. Omer Berat Sezer
2. M. Ugur Gudelek
3. Iqbal H. Sarker
4. Neda Tavakoli
5. M. Raja
6. A. Ozbayoglu

Papers from Sima Siami‐Namini's perspective

Ordered by how strongly the researchers Sima Siami‐Namini trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Forecasting Economics and Financial Time Series: ARIMA vs. LSTM (2018) — 279 citations
• A Comparison of ARIMA and LSTM in Forecasting Time Series (2018) — 1,065 citations
• The Performance of LSTM and BiLSTM in Forecasting Time Series (2019) — 1,361 citations