#ai #machinelearning #gnn #timeseries
Ever wondered what Graph Neural Networks can offer to your time series analysis?
Their capabilities in addressing time series challenges are vast, from enhancing route planning and managing congestion in smart cities to forecasting wind speed and power generation in the energy sector, as well as detecting fraud and predicting market trends in finance.
If you're not yet acquainted with the potential of GNNs, no need to worry!
We’ve organized a seminar where Dr. Ming Jin from Griffith University will provide a comprehensive review of GNNs for time series analysis and address key questions:
- What are GNNs, and how do they work with time series data?
- Why are GNNs crucial for analyzing complex dynamic systems?
- How can GNNs enhance real-world applications like traffic and energy predictions?
- What does the future hold for GNNs in time series analysis?
Негізгі бет MLBoost Seminars (10): Graph Neural Networks for Time Series
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