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Found 5 papers, 0 papers with code
DeepVARMA: A Hybrid Deep Learning and VARMA Model for Chemical Industry Index Forecasting
(2) In multivariate non-stationary series prediction, DeepVARMA uses a phased processing strategy to show higher adaptability and accuracy compared to the traditional VARMA model as well as the machine learning models LSTM, RF and XGBoost.
CLOP: Video-and-Language Pre-Training with Knowledge Regularizations
To this end, we propose a Cross-modaL knOwledge-enhanced Pre-training (CLOP) method with Knowledge Regularizations.
UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance
Diffusion generative models have recently greatly improved the power of text-conditioned image generation.
Temporal-Spatial dependencies ENhanced deep learning model (TSEN) for household leverage series forecasting
Analyzing both temporal and spatial patterns for an accurate forecasting model for financial time series forecasting is a challenge due to the complex nature of temporal-spatial dynamics: time series from different locations often have distinct patterns; and for the same time series, patterns may vary as time goes by.
A transfer learning enhanced the physics-informed neural network model for vortex-induced vibration
Vortex-induced vibration (VIV) is a typical nonlinear fluid-structure interaction phenomenon, which widely exists in practical engineering (the flexible riser, the bridge and the aircraft wing, etc).
