3 papers
math.NA2026
Risk-averse Optimization in Random Materials: Algorithmic Advances and HPC Acceleration
Niklas Baumgarten, Marcel Koch, David Schneiderhan +2
We summarize our advances in the algorithmic development and hardware utilization for risk-averse optimization problems in random materials. This includes risk-averse optimization…
math.OC2026
Multilevel Stochastic Gradient Descent for Risk-Averse PDE-Constrained Optimization
Niklas Baumgarten, Philipp A. Guth, David Schneiderhan +1
We present recent advances in applying and analyzing multilevel stochastic gradient descent algorithms to risk-averse, three-dimensional PDE-constrained optimization problems. The…
math.OC2025
Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty
Niklas Baumgarten, David Schneiderhan
We present a multilevel stochastic gradient descent method for the optimal control of systems governed by partial differential equations under uncertain input data. The gradient de…