Time-dependent series variance learning with recurrent mixture density networks

By Nikolay I. Nikolaev, Peter Tino, Evgueni Nikolaevich Smirnov. 2013

13 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Model Architectures, Signal Processing, Time-Series & Forecasting

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Omer Berat Sezer
2. M. Ugur Gudelek
3. A. Ozbayoglu

In Economics and Econometrics

1. Omer Berat Sezer
2. A. Ozbayoglu
3. M. Ugur Gudelek

In Model Architectures

1. M. Ugur Gudelek
2. A. Ozbayoglu
3. Omer Berat Sezer
4. Weiwei Jiang
5. Longbing Cao

In Signal Processing

1. A. Ozbayoglu
2. Omer Berat Sezer
3. M. Ugur Gudelek

In Time-Series & Forecasting

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Weiwei Jiang
5. Longbing Cao

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “In [164], RMDN with a GARCH (RMDN-GARCH) model was proposed.”