The presented approach to discretization of functionally defined heterogeneous objects is oriented towards applications associated with numerical simulation procedures, for exampl...
Elena Kartasheva, Valery Adzhiev, Alexander A. Pas...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
The Monte Carlo (MC) method is a simple but effective way to perform simulations involving complicated or multivariate functions. The QuasiMonte Carlo (QMC) method is similar but...
This review focuses on dynamic causal analysis of functional magnetic resonance (fMRI) data to infer brain connectivity from a time series analysis and dynamical systems perspecti...
Alard Roebroeck, Anil K. Seth, Pedro A. Valdes-Sos...
— Recent studies have shown that designing a Medium Access Control (MAC) protocol combined with a cooperative approach may improve the attainable network throughput, despite redu...