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Found 7 papers, 1 papers with code
Manifold Gaussian Variational Bayes on the Precision Matrix
We propose an optimization algorithm for Variational Inference (VI) in complex models.
Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots
Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series.
Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification
In addition, as the market evolves through time, it is necessary to update the existing models or train new ones when new data is made available.
Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning
Our Quasi Black-box Variational Inference (QBVI) framework is readily applicable to a wide class of Bayesian inference problems and is of simple implementation as the updates of the variational posterior do not involve gradients with respect to the model parameters, nor the prescription of the Fisher information matrix.
Bayesian Bilinear Neural Network for Predicting the Mid-price Dynamics in Limit-Order Book Markets
The prediction of financial markets is a challenging yet important task.
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction
Financial time-series forecasting is one of the most challenging domains in the field of time-series analysis.
Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting
Financial market analysis, especially the prediction of movements of stock prices, is a challenging problem.
