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FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns

Yitong Duan, Lei Wang, Qizhong Zhang, Jian Li
2022 AAAI Conference on Artificial Intelligence  
Essentially, our model integrates the dynamic factor model (DFM) with the variational autoencoder (VAE) in machine learning, and we propose a prior-posterior learning method based on VAE, which can effectively  ...  In this paper, we propose a novel factor model, FactorVAE, as a probabilistic model with inherent randomness for noise modeling.  ...  Acknowledgements The research is supported in part by the National Natural Science Foundation of China Grant 62161146004, Turing AI Institute of Nanjing and Xi'an Institute for Interdisciplinary Information  ... 
dblp:conf/aaai/DuanWZL22 fatcat:lpzpozzq6vbunkambvaxpmyxce

Machine learning approaches for time series problems

Χριστόφορος Στ. Ναλμπάντης
2022
The three main pillars of our contributions include novel machine learning architectures, time series embedding representations and designing deep learning models based on information theoretic principles  ...  We propose a new stacking machine learning system, a transfer learning mechanism that utilises imaging techniques for time series and three novel neural architectures.  ...  He offered me a great academic environment, surrounded by bright colleagues and always tried to support me financially.  ... 
doi:10.26262/heal.auth.ir.340363 fatcat:fqggq54crnaxpmaixk4go7kraa