Part of the Long Program Machine Learning for Physics and the Physics of Learning.
The workshop will include methods to summarize and interpret a complicated learned model (e.g. deep neural network) by interrogating this model about what and why it has learned (e.g. relevance propagation and sensitivity analysis).