Symposium on the Applications of Scientific Machine Learning

Scientific Machine Learning (SciML) is a rapidly emerging field in which conventional computational modeling is combined with machine learning techniques. By integrating domain knowledge and machine learning models, SciML has the potential to boost the performance of computational models and to reduce their computational cost. In this symposium, speakers will talk about real-world applications of SciML (and related methods) in diverse fields, ranging from financial risk modeling to weather forecasting and from computational chemistry to power grid control.

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