9 citations · 9 across the 4 of their papers we have counts for
5 papers
B-GRASP: A Bayesian Framework for Inferring Graph Weights from SPDE-Inspired Dynamics
Christina Schenk, Babak Maboudi Afkham
We present B-GRASP (Bayesian GRAph inference with SPDE priors), a Bayesian framework for inferring uncertain edge weights in stochastic dynamical systems on graphs from noisy obser…
Bayesian Optimization of Genetic Algorithm Hyperparameters in a Multi-Fidelity Framework for Efficient Lattice Material Design
Sergei Zorkaltsev, Maciej Haranczyk, Christina Schenk
This study presents a multi-fidelity framework for the systematic optimization of genetic algorithm (GA) hyperparameters. The framework integrates three fidelity levels: high-fidel…
Noise-Aware Optimization in Nominally Identical Manufacturing and Measuring Systems for High-Throughput Parallel Workflows
Christina Schenk, Miguel Hernández-del-Valle, Luis Calero-Lumbreras +2
Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While man…
A Novel Constrained Sampling Method for Efficient Exploration in Materials and Chemical Mixture Design
Christina Schenk, Maciej Haranczyk
Efficient exploration of multicomponent material composition spaces is often limited by time and financial constraints, particularly when mixture and synthesis constraints exist. T…
Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems
Christina Schenk, Aditya Vasudevan, Maciej Haranczyk +1
Mathematical and computational tools have proven to be reliable in decision-making processes. In recent times, in particular, machine learning-based methods are becoming increasing…