Conveners
Transients and Time Series: Session 1
- Giuliano Taffoni (University of Pisa and INFN-Pisa)
The latest advances in deep learning techniques have provided new effective prediction models that allow forecasting in detail the evolution of cosmogeophysical time series such as the solar activity, which is also crucial to anticipate potentially adverse space weather effects on the Earth’s environment.
Because of the underlying complexity of the quasi-periodic solar dynamo mechanism, the...
Exoplanet transit surveys produce flux time-series for
hundreds of thousands of stars to search for the tell-tale signs of a transiting planet. In the process, they provide a rich dataset for the application of machine learning (ML) methods. One focus so far has been the classification of exoplanet signals as genuine or instrumental false positives, particularly by using deep neural networks....
