In a network, pairs of individual elements, or nodes, connect to each other; those connections can represent a sprawling system with myriad individual links. A hypergraph goes deeper: It gives ...

A time series is a sequence of measurements performed at successive points in time. Time series can be used to derive models to predict future values based on previously observed values.

Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting ...

In this paper, we propose a novel approach called the Partially-Supervised Graph Derivation Network with Meta Learning (PS-GDNML) for time series anomaly detection. PS-GDNML combines the power of ...

A simple stock market price prediction app using Python, Streamlit, and basic ML models. It fetches historical stock data, makes predictions, and visualizes results interactively.

Abstract: In the field of multivariate time series prediction, capturing the dynamic relationships ... To address this challenge, our paper introduces MSPredictor, a multi-scale dynamic graph neural ...