7 papers
Non-Gaussianity of the Stagnation Law in Particle Swarm Optimization
Alexandra - Ionela Andriciuc, David - Corneliu Turturean, Ionel Popescu
We study one-dimensional particle swarm optimization during stagnation, with two fixed distinct attractors and equal independent uniform acceleration ranges. The position then sati…
Rank-One Fluctuations in Averaging-Learning Dynamics
Ionel Popescu, Tushar Vaidya
We study averaging-learning dynamics without an exogenous ground truth: the reference signal is generated endogenously by the population. The dynamics combine a time-varying averag…
Anchoring and Mixed-Norm Contractions in Averaging-Learning Dynamics
Ionel Popescu, Jeven Syatriadi, Tushar Vaidya
A single informed agent can draw an arbitrarily large network to the ground truth. This is the sharpest consequence of the "Averaging plus Learning" framework studied here, where a…
A self-supervised neural-analytic method to predict the evolution of COVID-19 in Romania
Radu D. Stochiţoiu, Marian Petrica, Traian Rebedea +2
Analysing and understanding the transmission and evolution of the COVID-19 pandemic is mandatory to be able to design the best social and medical policies, foresee their outcomes a…
Generic local identifiability for ODE inverse problems from discrete observations
Marian Petrica, Ionel Popescu
We study local identifiability of parameters in ordinary differential equation models from finitely many observations. The central object is the parameter-to-observation map obtain…
From Monte Carlo to neural networks approximations of boundary value problems
Lucian Beznea, Iulian Cimpean, Oana Lupascu-Stamate +2
In this paper we study probabilistic and neural network approximations for solutions to Poisson equation subject to Holder data in general bounded domains of . We aim…