4 papers
Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection
Geremy LoachamÃn-Suntaxi, Robert Lazar, Dimitrios G. Giovanis +2
Automating scientific computing workflows requires more than generating executable code: autonomous systems must also select appropriate computational strategies, implement them fa…
Optimal Transport, Timesteppers, Newton-Krylov Methods and Steady States of Collective Particle Dynamics
Hannes Vandecasteele, Nicholas Karris, Alexander Cloninger +1
Timesteppers constitute a powerful tool in modern computational science and engineering. Although they are typically used to advance the system forward in time, they can also be vi…
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do?
Anastasia Georgiou, Daniel Jungen, Luise Kaven +4
Bayesian Optimization (BO) with Gaussian Processes relies on optimizing an acquisition function to determine sampling. We investigate the advantages and disadvantages of using a de…
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
Nicholas Karris, Evangelos A. Nikitopoulos, Ioannis G. Kevrekidis +2
We develop an Euler-type method to predict the evolution of a time-dependent probability measure without explicitly learning an operator that governs its evolution. We use lineariz…