On Some Statistical and Machine Learning Problems in Research and Engineering

This talk will present a family of statistical (mixture of experts) distributions and ground their approximation and estimation properties related to their capabilities to deal with heterogenous data in high-dimensional and distributed/federated settings. It will also introduce approaches to leverage modern machine (deep) learning approaches with scientific and semantic knowledge to solve physical problems in engineering, including industrial design and supervision.

https://www.youtube.com/watch?v=0r_Bq2S72IA&list=PLhnghgyZINr9Z0wxdeBZhkbUjGuzI889A&index=3