Understanding Fourier Analysis: Uncovering Patterns in Time Series Data

Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.

Synchronizing ultrashort X-ray pulses for attosecond precision

Scientists at the Paul Scherrer Institute PSI have, for the first time, demonstrated a technique that synchronizes ultrashort ...
IEEE

A Novel Hybrid Architecture With Fast Lightweight Encoder and Transformer Under Attention Fusion for the Enhancement of Sand Dust and Haze Image Restoration

Abstract: Outdoor weather conditions such as haze, fog, sand dust, and low light significantly degrade image quality, causing color distortions, low contrast, and poor visibility. In spite of the ...
IEEE

DiffTST: Diff Transformer for Multivariate Time Series Forecast

Abstract: Deep learning models employing the Transformer architecture have demonstrated exceptional performance in the field of multivariate time series forecasting research. However, these models ...
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 ...
GitHub

Hierarchical Patch Based Transformer with Learnable Weighted Loss Optimization for Multivariate Time Series Forecasting (HPBTF)

Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...