8 citations · 11 across the 7 of their papers we have counts for
8 papers
Learning Optimal Power Flow with Pointwise Constraints
Damian Owerko, Anna Scaglione, Alejandro Ribeiro
Training learning parameterizations to solve optimal power flow (OPF) with pointwise constraints is proposed. In this novel training approach, a learning parameterization is substi…
MAST: Multi-Agent Spatial Transformer for Learning to Collaborate
Damian Owerko, Frederic Vatnsdal, Saurav Agarwal +2
This article presents a novel multi-agent spatial transformer (MAST) for learning communication policies in large-scale decentralized and collaborative multi-robot systems (DC-MRS)…
Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning
Shreyas Muthusamy, Damian Owerko, Charilaos I. Kanatsoulis +2
Unlabeled motion planning involves assigning a set of robots to target locations while ensuring collision avoidance, aiming to minimize the total distance traveled. The problem for…
Transferability of Convolutional Neural Networks in Stationary Learning Tasks
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk +2
Recent advances in hardware and big data acquisition have accelerated the development of deep learning techniques. For an extended period of time, increasing the model complexity h…
Solving Large-scale Spatial Problems with Convolutional Neural Networks
Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro
Over the past decade, deep learning research has been accelerated by increasingly powerful hardware, which facilitated rapid growth in the model complexity and the amount of data i…
Unsupervised Optimal Power Flow Using Graph Neural Networks
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Optimal power flow (OPF) is a critical optimization problem that allocates power to the generators in order to satisfy the demand at a minimum cost. Solving this problem exactly is…
Multi-Target Tracking with Transferable Convolutional Neural Networks
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk +2
Multi-target tracking (MTT) is a classical signal processing task, where the goal is to estimate the states of an unknown number of moving targets from noisy sensor measurements. I…
Optimal Power Flow Using Graph Neural Networks
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Optimal power flow (OPF) is one of the most important optimization problems in the energy industry. In its simplest form, OPF attempts to find the optimal power that the generators…