4 papers
Neural Co-state Policies: Structuring Hidden States in Recurrent Reinforcement Learning
David Leeftink, Max Hinne, Marcel van Gerven
A key capability of intelligent agents is operating under partial observability: reasoning and acting effectively despite missing or incomplete state observations. While recurrent…
Automated Discovery of Laser Dicing Processes with Bayesian Optimization for Semiconductor Manufacturing
David Leeftink, Roman Doll, Heleen Visserman +4
Laser dicing of semiconductor wafers is a critical step in microelectronic manufacturing, where multiple sequential laser passes precisely separate individual dies from the wafer.…
Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization
David Leeftink, Çağatay Yıldız, Steffen Ridderbusch +2
Without exact knowledge of the true system dynamics, optimal control of non-linear continuous-time systems requires careful treatment under epistemic uncertainty. In this work, we…
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo
Hester Huijsdens, David Leeftink, Linda Geerligs +1
Several disciplines, such as econometrics, neuroscience, and computational psychology, study the dynamic interactions between variables over time. A Bayesian nonparametric model kn…