Search Results - subject:"Convolutional networks"

Deep learning systems for forecasting the prices of crude oil and precious metals

Foroutan, Parisa; Lahmiri, Salim - In: Financial innovation : FIN 10 (2024), pp. 1-40

Commodity markets, such as crude oil and precious metals, play a strategic role in the economic development of nations, with crude oil prices influencing geopolitical relations and the global economy. Moreover, gold and silver are argued to hedge the stock and cryptocurrency markets during...

Persistent link: https://www.econbiz.de/10015361682

A Temporal Convolutional Network for modeling raw 3D sequences and air-writing recognition

Singh, Aradhana Kumari; Koundal, Deepika - In: Decision analytics journal 10 (2024), pp. 1-7

. Temporal Convolutional Networks (TCN) have been proposed for an air-writing recognition system. TCNs are variations of …

Persistent link: https://www.econbiz.de/10014533500

Constructing efficient simulated moments using temporal convolutional networks

Chassot, Jonathan; Creel, Michael D. - 2023

Persistent link: https://www.econbiz.de/10014445299

Statistical evaluation of deep learning models for stock return forecasting

Yilmaz, Firat Melih; Yildiztepe, Engin - In: Computational economics 63 (2024) 1, pp. 221-244

Persistent link: https://www.econbiz.de/10014472083

Explainable recommendation based on weighted knowledge graphs and graph convolutional networks

Boughareb, Rima; Seridi, Hassina; Beldjoudi, Samia - In: Journal of information & knowledge management : JIKM 22 (2023) 3, pp. 1-25

Persistent link: https://www.econbiz.de/10014388598

Dynamic relational graph convolutional network for metro passenger flow forecasting

He, Bisheng; Zhu, Yongjun; D'Ariano, Andrea; Wen, Keyu; … - In: Operations research forum 4 (2023) 4, pp. 1-27

Persistent link: https://www.econbiz.de/10014388692

Multi-layer and parallel-connected graph convolutional networks for detecting debt default in P2P networks

Lu, Shan; Wang, Yu; Liu, Xueyong; Jiang, Cheng - In: Emerging markets, finance & trade : a journal of the … 58 (2022) 6, pp. 1688-1701

Persistent link: https://www.econbiz.de/10013190184

Improving anti-money laundering in bitcoin using evolving graph convolutions and deep neural decision forest

Mohan, Anuraj; P.V., Karthika; Sankar, Parvathi; Maya … - In: Data Technologies and Applications 57 (2022) 3, pp. 313-329

Purpose Money laundering is the process of concealing unlawfully obtained funds by presenting them as coming from a legitimate source. Criminals use crypto money laundering to hide the illicit origin of funds using a variety of methods. The most simplified form of bitcoin money laundering leans...

Persistent link: https://www.econbiz.de/10014712696

Quant GANs : deep generation of financial time series

Wiese, Magnus; Knobloch, Robert; Korn, Ralf; … - In: Quantitative finance 20 (2020) 9, pp. 1419-1440

Persistent link: https://www.econbiz.de/10012313474

Forecasting jump arrivals in stock prices : new attention-based network architecture using limit order book data

Mäkinen, Ymir; Kanniainen, Juho; Gabbouj, Moncef; … - In: Quantitative finance 19 (2019) 12, pp. 2033-2050

Persistent link: https://www.econbiz.de/10015123063