Présidents de session
Frugal Unmixing, Reusing, and Sampling
- Christoph Weniger (University of Amsterdam)
Unmixing problems are ubiquitous in Physics, ranging from spectral unmixing to unsupervised component separation, where elementary physical components need to be separated out from intricate observed mixtures. These problems are generally ill-posed, which mandates the design of effective regularisation to better distinguish between the sought-after components. While ML-based methods are...
With the increasing usage of machine learning in high energy physics analyses, the publication of the learned models in a reusable form has become a crucial question for analysis preservation and reuse. In turn, a lack of appropriate ML design and publication makes reinterpretation of analyses in terms of physics scenarios beyond those considered in the original experimental paper seriously...
This workshop gathered experts in computational methods for rare events sampling interested in machine learning methods and experts in generative models interested in applications to physical systems. In this talk I will try to summarize the main directions of research that...
