GitHub

Is Mamba Effective for Time Series Forecasting?

We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...
IEEE

Physics-Informed LSTM-Based Time-Series Forecasting Model for Power Transformers

Abstract: The complexity of data and limited model generalization significantly hinder prediction accuracy. A physics-informed long short-term memory model with adaptive weight assignment (PILSTM-AWA) ...
GitHub

Time Series Forecasting Engine

Time Series Forecasting Engine is a comprehensive, production-ready Python framework for advanced time series forecasting. It combines statistical models (ARIMA), machine learning approaches (Prophet) ...
TV Insider

The 25 Best Disney+ Original Series, Ranked

Disney+ touts an attractive catalog as the streaming home of Marvel and Star Wars. The platform launched in November 2019 with the first live-action Star Wars original series, The Mandalorian, and ...
IEEE

An Attention-based LSTM price prediction model based on a single time series information

Abstract: With the continuous improvement of people's living standards, people's income from work has gradually increased, and their remaining savings have also gradually increased. In order to avoid ...
TV Insider

The Best 25 Peacock Original Series, Ranked

Peacock has a little bit of everything. The streaming home of Saturday Night Live and the Law & Order franchise keeps the NBC vibes going on its platform with a collection of originals that reflect a ...
Frontiers

Human intention recognition by deep LSTM and transformer networks for real-time human-robot collaboration

Humanoid and Cognitive Robotics Laboratory, Department of Automatics, Biocybernetics, and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia Collaboration between humans and robots is essential for ...