Speaker
Dr
Gael Varoquaux
(INRIA)
Description
How do we model and reason with machine learning? Machine learning models typically do not build upon mechanistic assumptions. I will discuss important concepts required to gauge machine-learning model outputs, in particular controling their uncertainty and wether they support causal reasonning. I will also discuss implicit modeling (inductive biases), contrasting tree-based models with neural networks.
