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- 12:30 CRI - Learning Center Extension

CRI Research Collaboratory seminar - Remy Kusters

CRI Research Collaboratory seminar - Remy Kusters

Deep learning driven model discovery in biology and physics

Remy Kusters- CRI

As scientific data sets become richer and increasingly complex, machine learning (ML) tools become more useful and widely applied. Discovering a mechanistic model, rather than predicting the outcome is paramount in the scientific endeavor and its lack in present day ML is limiting further integration of ML in quantitative science. In this talk I will present our development of quantitative tools to extract human interpretable models from quantitative biological and physical data sets. The work combines the predictive power of neural networks with the interpretability of symbolic regression to develop a framework of interpretable AI and discover mechanistic models from biological and physical data.


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