Presentation of the HDA 2019

Numerical approximation in high-dimensional spaces has, in the past decade, emerged as a key mathematical and computational theme at the intersection of several broad research areas in applied and computational mathematics. HDA is a series of informal, bi-annual workshops
which serves as forum for researchers to exchange ideas and co-ordinate research agendas at the forefront of high-dimensional approximation and computation.

The 2019 edition of the HDA conference at ETH Zurich continues the HDA series of bi-annual meetings initiated at ANU in Canberra (HDA05) which has alternated between external pageINS, Bonn, external pageUNSW, Sydney and external pageANU, Canberra.

Topics include, but are not limited to

- Sparse grid methods
- Quasi-Monte Carlo methods
- Tensor decompositions
- Polynomial chaos expansions
- Sparse approximations
- Reduced basis methods
- Multi-level methods
- Bayesian inversion
- Uncertainty quantification
- Manifold learning
- Nonlinear dimensionality reduction