The course sets up the foundations and covers the basic algorithms covered in probabilistic machine learning. Several techniques that are probabilistic in nature are introduced and standard topics are ...

An interview with Karl Friston, a computational psychiatrist and an architect of an AI developed to emulate natural ...

Nano-architected materials combine highly efficient shapes similar to triangular structures in bridges, but at the nanoscale, ...

Researchers at the University of Toronto have created this stunning material by merging machine learning (AI) with nanoscale ...

The KAIST team employed the multi-objective Bayesian optimization machine learning algorithm. This algorithm learned from simulated geometries to predict the best possible geometries for enhancing ...

A research group has developed SPACIER, an advanced polymer material design tool that integrates machine learning with ...

Researchers have used machine learning to design nanoarchitected materials that are very light and very strong.

The KAIST team employed the multi-objective Bayesian optimization machine learning algorithm. This algorithm learned from simulated geometries to predict the best possible geometries for enhancing ...

The ideal candidate has a strong background in computational statistics and/or machine learning, and experience with Bayesian machine learning methods (e.g., Gaussian processes, variational inference, ...