Seminar: On Adaptive Multilevel Monte Carlo and Multi-Index Monte Carlo By Prof. Raul Tempone (KAUST)
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We provide a quick glance into recently developed Adaptive Multilevel Monte Carlo (MLMC) Methods for the following widely applied mathematical models: (i) Itô Stochastic Differential Equations, (ii) Stochastic Reaction Networks modeled by Pure Jump Markov Processes, and (iii) Partial Differential Equations with random inputs. In this context, the notion of adaptivity includes several aspects such as mesh refinements based on either a priori or a posteriori error estimates, the local choice of different time-stepping methods, and the selection of the total number of levels and the number of samples at different levels.
About
- Class schedule: Thursday Nov. 6th, 2014, 03:00pm -04:00pm
- Location: Building 9, Room 2322
- Refreshments: Available @ 01:45pm
