Search Results - subject:"Autoencoder"

Asset pricing via the conditional quantile variational autoencoder

Yang, Xuanling; Zhu, Zhoufan; Li, Dong; Zhu, Ke - In: Journal of business & economic statistics : JBES ; a … 42 (2024) 2, pp. 681-694

Persistent link: https://www.econbiz.de/10015053443

Quantifying credit portfolio sensitivity to asset correlations with interpretable generative neural networks

Caprioli, Sergio; Cagliero, Emanuele; Crupi, Riccardo - In: The journal of risk model validation 18 (2024) 1, pp. 1-17

Persistent link: https://www.econbiz.de/10014556697

Evolutionary multi-objective design of autoencoders for compact representation of histopathology whole slide images

Zaman Farsa, Davood; Rahnamayan, Shahryar; Bidgoli, … - In: Computers & operations research : an international journal 162 (2024), pp. 1-15

Persistent link: https://www.econbiz.de/10014560612

Handling massive sparse data in recommendation systems

Chetana, V. Lakshmi; Seetha, Hari - In: Journal of information & knowledge management : JIKM 23 (2024) 3, pp. 1-37

Persistent link: https://www.econbiz.de/10014575739

Development of Honey Badger-Cat Swarm optimisation-based parallel cascaded deep network for software bug prediction framework

Gupta, Anurag; Sharma, Mayank; Srivastava, Amit - In: Journal of information & knowledge management : JIKM 23 (2024) 3, pp. 1-35

Persistent link: https://www.econbiz.de/10014575898

Risk factor aggregation and stress testing

Packham, Natalie - In: Quantitative finance 24 (2024) 9, pp. 1327-1340

Persistent link: https://www.econbiz.de/10015196926

Regularization of autoencoders for bank client profiling based on financial transactions

Filchenkov, Andrey; Khanzhina, Natalia; Tsai, Arina; … - In: Risks 9 (2021) 3, pp. 1-16

verify our hypothesis applying data driven regularized classification using an autoencoder to client profiles. To model an … intention as a hidden variable, we propose an especially designed regularizer for the autoencoder. The regularizer aims to …

Persistent link: https://www.econbiz.de/10013200723

An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination

Gunduz, Hakan - In: Financial Innovation 7 (2021) 1, pp. 1-24

In this study, the hourly directions of eight banking stocks in Borsa Istanbul were predicted using linear-based, deep-learning (LSTM) and ensemble learning (LightGBM) models. These models were trained with four different feature sets and their performances were evaluated in terms of accuracy...

Persistent link: https://www.econbiz.de/10012602909

Understanding corporate default using Random Forest : the role of accounting and market information

Bitetto, Alessandro; Filomeni, Stefano; Modina, Michele - 2021

Persistent link: https://www.econbiz.de/10012887215

Regularization of autoencoders for bank client profiling based on financial transactions

Filchenkov, Andrey; Khanzhina, Natalia; Tsai, Arina; … - In: Risks : open access journal 9 (2021) 3, pp. 1-16

Persistent link: https://www.econbiz.de/10012508541