A Comparison of ARIMA and LSTM in Forecasting Time Series S Siami-Namini, A Tavakoli, A Siami Namin IEEE, 2018 | 1192 | 2018 |
The performance of LSTM and BiLSTM in forecasting time series S Siami-Namini, N Tavakoli, AS Namin 2019 IEEE International conference on big data (Big Data), 3285-3292, 2019 | 975 | 2019 |
Forecasting Economics and Financial Time Series: ARIMA vs. LSTM S Siami-Namini, A Siami Namin arXiv preprint arXiv:1803.06386, 2018 | 330 | 2018 |
Inflation and Income Inequality in Developed and Developing Countries S Siami-Namini, D Hudson Journal of Economic Studies; SSRN Electronic Journal 46 (3), 611-632, 2019 | 114 | 2019 |
A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM S Siami-Namini, N Tavakoli, A Siami Namin | 113 | 2019 |
Can machine/deep learning classifiers detect zero-day malware with high accuracy? F Abri, S Siami-Namini, MA Khanghah, FM Soltani, AS Namin 2019 IEEE international conference on big data (Big Data), 3252-3259, 2019 | 64 | 2019 |
Forecasting economics and financial time series: ARIMA vs S Siami-Namini, AS Namin LSTM. arXiv 1803, 2018 | 64 | 2018 |
An autoencoder‑based deep learning approach for clustering time series data N Tavakoli, S Siami‑Namini, M Adl Khanghah, F Mirza Soltani, ... SN Applied Science 2 (937), 2020 | 49 | 2020 |
A comparison of TCN and LSTM models in detecting anomalies in time series data S Gopali, F Abri, S Siami-Namini, AS Namin 2021 IEEE International Conference on Big Data (Big Data), 2415-2420, 2021 | 33 | 2021 |
Granger causality between exchange rate and stock price: A Toda Yamamoto approach S Siami-Namini International Journal of Economics and Financial Issues 7 (4), 603-607, 2017 | 30 | 2017 |
The Impacts of Sector Growth and Monetary Policy on Income Inequality in Developing Countries S Siami-Namini, D Hudson Journal of Economic Studies; Available at SSRN 3059381 46 (3), 591-610, 2019 | 26 | 2019 |
Volatility Transmission Among Oil Price, Exchange Rate and Agricultural Commodities Prices S Siami-Namini Applied Economics and Finance 6 (4), 41-61, 2019 | 22 | 2019 |
Commodity Price Volatility and U.S. Monetary Policy: Commodity Price Overshooting Revisited S Siami-Namini, D Hudson, AA Trindade, C Lyford Agribusiness 35 (2), 200-218, 2019 | 19 | 2019 |
Healthcare expenditure, economic growth, and inflation in the G7 countries: A panel cointegration approach S Siami-Namini Research Journal of Economics 2 (2), 2018 | 13* | 2018 |
Volatility spillover between oil prices, US dollar exchange rates and international agricultural commodities prices S Siami-Namini, D Hudson Presentation at the 2017 Annual Meeting of the Southern Agricultural …, 2017 | 13 | 2017 |
Using experiential learning to teach and learn digital forensics: Educator and student perspectives R Flores, AS Namin, N Tavakoli, S Siami-Namini, KS Jones Computers and Education Open 2, 100045, 2021 | 12 | 2021 |
Clustering time series data through autoencoder-based deep learning models N Tavakoli, S Siami-Namini, MA Khanghah, FM Soltani, AS Namin arXiv preprint arXiv:2004.07296, 2020 | 12 | 2020 |
A comparative study of detecting anomalies in time series data using LSTM and TCN models S Gopali, F Abri, S Siami-Namini, AS Namin arXiv preprint arXiv:2112.09293, 2021 | 11 | 2021 |
Knowledge Management Challenges in Public Sectors S Siami-Namini Research Journal of Economics 2 (3), 1-9, 2018 | 11 | 2018 |
US Monetary Policy and Commodities Price Fluctuations S Siami-Namini, D Hudson | 11 | 2016 |