IEEE

Fusion Graph Structure Learning-Based Multivariate Time Series Anomaly Detection With Structured Prior Knowledge

Abstract: Multivariate time series anomaly detection (MTSAD) plays a crucial role in the Internet of Things (IoT) to identify device malfunction or system attacks. Graph neural networks (GNN) are ...
IEEE

Graph Structure Learning-Based Multivariate Time Series Anomaly Detection in Internet of Things for Human-Centric Consumer Applications

Abstract: As the Internet of Things system becomes more popular and ubiquitous, it has also gradually entered the consumer electronics field. For example, smart home systems have numerous sensors that ...
Hosted on MSN

4e example 1 (how to graph the sine function)

I make short, to-the-point online math tutorials. I struggled with math growing up and have been able to use those experiences to help students improve in math through practical applications and tips.
GitHub

simple_agent_example.py

"""Call to surf the web.""" # 実際に検索していないことはLLMにナイショにしておいてね if "sf" in query.lower() or "san francisco" in query.lower(): return "It's 60 degrees and foggy." return "It's 90 degrees and sunny." # ...
Scientific Research Publishing

Cini, A., Marisca, I. and Alippi, C. (2021) Filling the Gaps: Multivariate Time Series Imputation by Graph Neural Networks. arXiv:2108.00298.

ABSTRACT: Air pollution has become a pressing challenge to global public health and environmental governance. Accurate analysis of pollutant concentrations critically depends on the completeness of ...