5 papers
Goal-Oriented Adaptive Finite Element Multilevel Quasi-Monte Carlo
Joakim Beck, Yang Liu, Erik von Schwerin +1
The efficient approximation of quantities of interest derived from PDEs with lognormal diffusivity is a central challenge in uncertainty quantification. This paper targets a proble…
Pontryagin-Based Solver with Smoothed Hamiltonian, Adaptive , and PA-Bundle Refinement
Salim Ksous, Sebastian Lalvay Segovia, Mattias Sandberg +3
We present a Pontryagin-based numerical solver for deterministic optimal control problems in Bolza form. The solver regularizes the generally nonsmooth Hamiltonian using a log-sum-…
Convergence for adaptive resampling of random Fourier features
Xin Huang, Aku Kammonen, Anamika Pandey +4
The machine learning random Fourier feature method for data in high dimension is computationally and theoretically attractive since the optimization is based on a convex standard l…
A Pontryagin Maximum Principle on the Belief Space for Continuous-Time Optimal Control with Discrete Observations
Christian Bayer, Saifeddine Ben naamia, Erik von Schwerin +1
We study a continuous time stochastic optimal control problem under partial observations that are available only at discrete time instants. This hybrid setting, with continuous dyn…
Adaptive Random Fourier Features Training Stabilized By Resampling With Applications in Image Regression
Aku Kammonen, Anamika Pandey, Erik von Schwerin +1
This paper presents an enhanced adaptive random Fourier features (ARFF) training algorithm for shallow neural networks, building upon the work introduced in "Adaptive Random Fourie…