96 citations · 124 across the 9 of their papers we have counts for
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cs.LG2020★ 12 cited
Clustering Time Series Data through Autoencoder-based Deep Learning Models
Neda Tavakoli, Sima Siami-Namini, Mahdi Adl Khanghah +2
Machine learning and in particular deep learning algorithms are the emerging approaches to data analysis. These techniques have transformed traditional data mining-based analysis r…
cs.LG2020★ 1 cited
Locality Sensitive Hashing-based Sequence Alignment Using Deep Bidirectional LSTM Models
Neda Tavakoli
Bidirectional Long Short-Term Memory (LSTM) is a special kind of Recurrent Neural Network (RNN) architecture which is designed to model sequences and their long-range dependencies…
cs.LG2019★ 96 cited
A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM
Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin
Machine and deep learning-based algorithms are the emerging approaches in addressing prediction problems in time series. These techniques have been shown to produce more accurate r…