2 citations · 2 across the 6 of their papers we have counts for
6 papers
A first-optimize-then-reduce framework for optimal control with the shifted proper orthogonal decomposition
Tobias Breiten, Shubhaditya Burela, Philipp Schulze
Overcoming the Kolmogorov barrier for constructing efficient reduced-order models (ROMs) for transport-dominated problems remains a challenge. This has impeded their use as computa…
Optimal control for a class of linear evolution equations with transformed proper orthogonal decomposition
Tobias Breiten, Shubhaditya Burela, Philipp Schulze
Solving optimal control problems for high-dimensional partial differential equations (PDEs) is computationally expensive. As a workaround, reduced-order models (ROMs) are often emp…
Optimal control for a class of linear transport-dominated systems via the shifted proper orthogonal decomposition
Tobias Breiten, Shubhaditya Burela, Philipp Schulze
Solving optimal control problems for transport-dominated partial differential equations (PDEs) can become computationally expensive, especially when dealing with high-dimensional s…
Automated transport separation using the neural shifted proper orthogonal decomposition
Beata Zorawski, Shubhaditya Burela, Philipp Krah +2
This paper presents a neural network-based methodology for the decomposition of transport-dominated fields using the shifted proper orthogonal decomposition (sPOD). Classical sPOD…
Parametric model order reduction for a wildland fire model via the shifted POD based deep learning method
Shubhaditya Burela, Philipp Krah, Julius Reiss
Parametric model order reduction techniques often struggle to accurately represent transport-dominated phenomena due to a slowly decaying Kolmogorov n-width. To address this challe…
Hessian Chain Bracketing
Uwe Naumann, Shubhaditya Burela
Second derivatives of mathematical models for real-world phenomena are fundamental ingredients of a wide range of numerical simulation methods including parameter sensitivity analy…