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  • Search: subject:"Generative adversarial networks"
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Year of publication
Subject
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generative adversarial networks 8 Theorie 5 Theory 5 Artificial intelligence 4 Generative adversarial networks 4 Künstliche Intelligenz 4 Neural networks 4 Neuronale Netze 4 Estimation 3 Schätzung 3 Aesthetics 2 Estimation theory 2 Forecasting model 2 Innovation 2 LSV calibration 2 New product development 2 Product design 2 Produktentwicklung 2 Produktgestaltung 2 Prognoseverfahren 2 Schätztheorie 2 Simulation 2 deep hedging 2 indirect inference 2 machine learning 2 neural SDEs 2 neuralnetworks 2 simulated method of moments 2 stochastic optimization 2 structural estimation 2 variance reduction 2 Ästhetik 2 Anomaly detection deep learning 1 Arbeitsmobilität 1 Artificial Neural Networks 1 Attributed networks autoencoder 1 Automated fiber placement 1 Business network 1 Cluster analysis 1 Clusteranalyse 1
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Online availability
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Free 14 CC license 6
Type of publication
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Article 11 Book / Working Paper 3
Type of publication (narrower categories)
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Article in journal 9 Aufsatz in Zeitschrift 9 Working Paper 3 Arbeitspapier 2 Article 2 Graue Literatur 2 Non-commercial literature 2
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Language
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English 14
Author
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Kaji, Tetsuya 3 Manresa, Elena 3 Pouliot, Guillaume 3 Burnap, Alex 2 Cuchiero, Christa 2 Hauser, John R. 2 Khosrawi, Wahid 2 Teichmann, Josef 2 Timoshenko, Artem 2 Abidin, Shafiqul 1 Ahmed, Imtiaz 1 Arif, Mohammad 1 Boot, Tom 1 Das, Srinjoy 1 Dumisani Selby Nkambule 1 Faisal, Syed Mohd 1 Farhadpour, Sarah 1 Farooqui, Nafees Akhtar 1 Flaig, Thekla Solveig 1 Groves, Roger M. 1 Haleem, Mohd 1 Ishrat, Mohammad 1 Jiang, He 1 Junike, Gero 1 Khan, Wasim 1 Khosravi, Hamed 1 Lv, Mengzheng 1 Meister, Sebastian 1 Möller, Nantwin 1 Ponte, Gilian R. 1 Pretorious, Jan Harm Christiaan 1 Shafie, Mohammad Reza 1 Shaikh, Anwar Ahamed 1 Stüve, Jan 1 Twala, Bhekisipho 1 Verhoef, Peter C. 1 Wang, Jianzhou 1 Wang, Shuai 1 Wieringa, Jaap E. 1
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Published in...
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Risks : open access journal 3 CEMMAP working papers / Centre for Microdata Methods and Practice 1 Data science and management : DSM 1 Decision analytics journal 1 Econometrica : journal of the Econometric Society, an international society for the advancement of economic theory in its relation to statistics and mathematics 1 Financial innovation : FIN 1 International journal of research in marketing : IJRM ; official journal of the European Marketing Academy 1 Journal of Intelligent Manufacturing 1 MIT Sloan Research Paper 1 Marketing science 1 Risks 1 cemmap working paper 1
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Source
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ECONIS (ZBW) 11 EconStor 3
Showing 1 - 10 of 14
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Effective machine learning techniques for dealing with poor credit data
Dumisani Selby Nkambule; Twala, Bhekisipho; Pretorious, … - In: Risks : open access journal 12 (2024) 11, pp. 1-19
and MCC metrics. Then, the harnessing of generative adversarial networks (GANs) simulation to enhance the robustness of …
Persistent link: https://www.econbiz.de/10015135786
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Forecasting VaR and ES by using deep quantile regression, GANs-based scenario generation, and heterogeneous market hypothesis
Wang, Jianzhou; Wang, Shuai; Lv, Mengzheng; Jiang, He - In: Financial innovation : FIN 10 (2024), pp. 1-35
and employs generative adversarial networks to generate future tail risk scenarios. In addition to the typical properties …
Persistent link: https://www.econbiz.de/10014530222
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Where's Waldo? : a framework for quantifying the privacy-utility trade-off in marketing applications
Ponte, Gilian R.; Wieringa, Jaap E.; Boot, Tom; … - In: International journal of research in marketing : IJRM ; … 41 (2024) 3, pp. 529-546
Persistent link: https://www.econbiz.de/10015057560
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Anomalous node detection in attributed social networks using dual variational autoencoder with generative adversarial networks
Khan, Wasim; Abidin, Shafiqul; Arif, Mohammad; Ishrat, … - In: Data science and management : DSM 7 (2024) 2, pp. 89-98
Many types of real-world information systems, including social media and e-commerce platforms, can be modelled by means of attribute-rich, connected networks. The goal of anomaly detection in artificial intelligence is to identify illustrations that deviate significantly from the main...
Persistent link: https://www.econbiz.de/10015063137
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A cluster-based human resources analytics for predicting employee turnover using optimized Artificial Neural Networks and data augmentation
Shafie, Mohammad Reza; Khosravi, Hamed; Farhadpour, Sarah; … - In: Decision analytics journal 11 (2024), pp. 1-17
Adversarial Networks (CTGAN) is performed on clusters with imbalanced data. Following this, the optimized ANN models are applied … implemented to improve the efficiency and effectiveness of retention policies. Data augmentation using Conditional Generative …
Persistent link: https://www.econbiz.de/10015101907
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Product aesthetic design : a machine learning augmentation
Burnap, Alex; Hauser, John R.; Timoshenko, Artem - In: Marketing science 42 (2023) 6, pp. 1029-1056
Persistent link: https://www.econbiz.de/10014436737
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An adversarial approach to structural estimation
Kaji, Tetsuya; Manresa, Elena; Pouliot, Guillaume - In: Econometrica : journal of the Econometric Society, an … 91 (2023) 6, pp. 2041-2063
Persistent link: https://www.econbiz.de/10014438258
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Scenario generation for market risk models using generative neural networks
Flaig, Thekla Solveig; Junike, Gero - In: Risks : open access journal 10 (2022) 11, pp. 1-28
In this research study, we show how existing approaches of using generative adversarial networks (GANs) as economic …
Persistent link: https://www.econbiz.de/10013556779
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Product Aesthetic Design : A Machine Learning Augmentation
Burnap, Alex; Hauser, John R.; Timoshenko, Artem - 2022
variational autoencoder (VAE), adversarial components from generative adversarial networks (GAN), and a supervised learning …
Persistent link: https://www.econbiz.de/10014242270
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Synthetic image data augmentation for fibre layup inspection processes: Techniques to enhance the data set
Meister, Sebastian; Möller, Nantwin; Stüve, Jan; … - In: Journal of Intelligent Manufacturing 32 (2021) 6, pp. 1767-1789
In the aerospace industry, the Automated Fiber Placement process is an established method for producing composite parts. Nowadays the required visual inspection, subsequent to this process, typically takes up to 50% of the total manufacturing time and the inspection quality strongly depends on...
Persistent link: https://www.econbiz.de/10014502064
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