A machine learning accelerated inverse design of underwater acoustic polyurethane coatings with cylindrical voids

no code implementations • 2 Mar 2022 • Hansani Weeratunge, Zakiya Shireen, Sagar Iyer, Richard Sandberg, Saman Halgamuge, Adrian Menzel, Andrew Phillips, Elnaz Hajizadeh

Here, we report the development of a detailed "Materials Informatics" framework for the design of acoustic coatings for underwater sound attenuation through integrating Machine Learning (ML) and statistical optimization algorithms with a Finite Element Model (FEM).

Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems

1 code implementation • 28 May 2019 • Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds

Our model class is a generalisation of nonlinear mixed-effects (NLME) dynamical systems, the statistical workhorse for many experimental sciences.

Bayesian Inference Zero-Shot Learning