Bayesian Neural Networks for Bridging the Gap Between Machine Learning and Econometrics

Project Information

BNNmetrics

Grant agreement ID: 890690

DOI

10.3030/890690

Project closed

EC signature date 25 March 2020

Start date 1 October 2020

End date 30 September 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 207 312,00

EU contribution

€ 207 312,00

Coordinated by

AARHUS UNIVERSITET
Denmark

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Other (5)

Bayesian Learning for Neural Networks: an algorithmic survey

Author(s): Martin Magris, Alexandros Iosifidis
Published in: ArXiv Preprint, 2022
Publisher: arxiv.org

Quasi Black-Box Variational Inference with NaturalGradients for Bayesian Learning

Author(s): Martin Magris, Mostafa Shabani, Alexandros Iosifidis
Published in: ArXiv Preprint, 2022
Publisher: ArXiv

Exact manifold Gaussian Variational Bayes

Author(s): Martin Magris, Mostafa Shabani, Alexandros Iosifidis
Published in: ArXiv Preprint, 2022
Publisher: ArXiv

Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots

Author(s): Mostafa Shabani, Martin Magris, George Tzagkarakis, Juho Kanniainen, Alexandros Iosifidis
Published in: ArXiv Preprint, 2022
Publisher: ArXiv

Bayesian Bilinear Neural Network for Predicting the Mid-price Dynamics in Limit-Order Book Markets

Author(s): Martin Magris, Mostafa Shabani, Alexandros Iosifidis
Published in: ArXiv Preprint, 2022
Publisher: ArXiv