Multivariate functions arise naturally in statistics, uncertainty quantification, optimal control, quantum mechanics and other applications. There exist different ways of working with high-dimensional functions and data: sampling, polynomial approximations, separation of variables. Depending on assumptions, one or another of these techniques might be preferable. Even more promising might be a combination of those.

The workshop will include several talks on high-dimensional algorithms and applications, as well as opportunity to discuss further development of this area.

Programme

Thursday, 22nd November

• 8:30 - 9:00 Arrival
  
• 9:00 - 9:50 Tiangang Cui (Monash University): TBA
• 9:50 - 10:10 Coffee break
• 10:10 - 11:00 Dante Kalise (Imperial College London): TBA
• 11:00 - 11:50 John Pearson (University of Edinburgh): TBA
• 11:50 - 13:00 Lunch
• 13:00 - 17:00 Free time/discussion
• 19:00 Dinner

Friday 23rd November

• 9:00 - 9:50 Dirk Nuyens (KU Leuven): TBA
• 9:50 - 10:10 Coffee break
• 10:10 - 11:00 Dmitry Savostyanov (University of Brighton): TBA
• 11:00 - 11:50 Sebastian Krämer (RWTH Aachen): TBA
• 11:50 Close

All talks will be in Wolfson Lecture Theatre (room 1.7) of the 4 West building. Coffee and lunch will be served on the first floor of 4 West, outside of the Wolfson Lecture Theatre.

We gratefully acknowledge support from EPSRC through a Postdoctoral Fellowship EP/M019004/1.