4 papers · 1 filter
Privileged observations enable rapid and reliable policy discovery directly in the physical world
Antonio Terpin, Raffaello D'Andrea
We study how privileged information about a physical system affects the discovery of high-performing policies when training a reinforcement learning agent directly in the physical…
Flow Gym: A framework for the development, benchmarking, training, and deployment of flow-field quantification methods
Francesco Banelli, Antonio Terpin, Alan Bonomi +1
Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluation are often hindered by fragmented so…
SynthPix: A lightspeed PIV image generator
Antonio Terpin, Alan Bonomi, Francesco Banelli +1
We describe SynthPix, a synthetic image generator for Particle Image Velocimetry (PIV) with a focus on performance and parallelism on accelerators, implemented in JAX. SynthPix pro…
Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers
Panagiotis D. Grontas, Antonio Terpin, Efe C. Balta +2
We introduce an output layer for neural networks that ensures satisfaction of convex constraints. Our approach, net, leverages operator splitting for rapid and reliable projecti…