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 page INS, Bonn, external page UNSW, Sydney and external page ANU, 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