5 papers
A Bayesian-optimization framework coupling a multiphase PDE tumor model to efficiently design combination therapy schedules
Ioannis Lampropoulos, Yorgos Psarellis, Michail Kavousanakis
Designing combination cancer therapies requires choosing not only which agents to combine but also their relative doses and timing decisions that critically shape the trade-off bet…
The Right Space for Dynamics: Numerics with Diffeomorphism Equivariance
Wolf-Juergen Beyn, Michail E. Kavousanakis, Yannis G. Kevrekidis
Among many (equivalent, via invertible transformations) representations of the evolution of a dynamical system, which one is to be preferred? Here we show how the use of infinite-d…
Singularities in Multi-Objective Optimization and their Crossing during Continuation
Arjun Manoj, Michail E. Kavousanakis, Shanqing Liu +1
Continuation methods help trace Pareto sets in multi-objective optimization but are inherently local: a single run traces a single connected branch, requiring multiple restarts to…
Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach
Gianluca Fabiani, Michail E. Kavousanakis, Constantinos Siettos +1
We address a numerical framework for the stability and bifurcation analysis of nonlinear partial differential equations (PDEs) in which the solution is sought in the function space…
A Physics Informed Machine Learning Framework for Optimal Sensor Placement and Parameter Estimation
Georgios Venianakis, Constantinos Theodoropoulos, Michail Kavousanakis
Parameter estimation remains a challenging task across many areas of engineering. Because data acquisition can often be costly, limited, or prone to inaccuracies (noise, uncertaint…