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In this work, we investigate various approaches that use learning from training data to solve inverse problems, following a bi-level learning approach. We consider a general framework for optimal inversion design, where...

In this paper, we propose a parking allocation model that takes into account the basic constraints and objectives of a problem where parking lots are assigned to vehicles. We assume vehicles are connected and can exchange...

We develop a multi-country general equilibrium model featuring (i) migration flows across borders; (ii) explicit supply chain networks both across sectors and across countries; (iii) services sector with a significant role in...

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the motion of virtual particles within a multidimensional space. The particles explore the space in an attempt to find minima or maxima to the...

This paper presents a novel distributed control strategy for large-scale deployment of flexible demand in power systems. A game theoretical setting is adopted, modeling the loads as rational players that aim to complete an...

This paper puts Search Frictions models under novel empirical scrutiny. To capture changing dynamics, we fit a Bayesian time-varying parameter VAR to US labour market data from 1965–2016. Using a DSGE model with Search...

We propose a mean-field optimal control problem for the parameter identification of a given pattern. The cost functional is based on the Wasserstein distance between the probability measures of the modeled and the desired...

In this paper, we propose a parking allocation model that takes into account the basic constraints and objectives of a problem where parking lots are assigned to vehicles. We assume vehicles are connected and can exchange...

We propose a mean-field optimal control problem for the parameter identification of a given pattern. The cost functional is based on the Wasserstein distance between the probability measures of the modeled and the desired...

We consider a statistical inverse learning problem, where the task is to estimate a function f based on noisy point evaluations of Af, where A is a linear operator. The function Af is evaluated at i.i.d. random design points...

This paper presents a novel distributed control strategy for large-scale deployment of flexible demand in power systems. A game theoretical setting is adopted, modeling the loads as rational players that aim to complete an...

We develop a multi-country general equilibrium model featuring (i) migration flows across borders; (ii) explicit supply chain networks both across sectors and across countries; (iii) services sector with a significant role in...

This paper presents a novel cable-driven exoskeleton (BiEXO) for the upper limb including shoulder and elbow joints. BiEXO is made of carbon fiber that is inspired by the Bamboo structure. The key components of BiEXO are...

A wide range of applications for which unmanned aerial vehicles (UAVs) are ideally suited rely on the development of manipulators capable of exchanging forces with the environment. One such application is the installation and...

This paper puts Search Frictions models under novel empirical scrutiny. To capture changing dynamics, we fit a Bayesian time-varying parameter VAR to US labour market data from 1965–2016. Using a DSGE model with Search...

This paper presents a novel cable-driven exoskeleton (BiEXO) for the upper limb including shoulder and elbow joints. BiEXO is made of carbon fiber that is inspired by the Bamboo structure. The key components of BiEXO are...

In this work, we investigate various approaches that use learning from training data to solve inverse problems, following a bi-level learning approach. We consider a general framework for optimal inversion design, where...

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the motion of virtual particles within a multidimensional space. The particles explore the space in an attempt to find minima or maxima to the...

A wide range of applications for which unmanned aerial vehicles (UAVs) are ideally suited rely on the development of manipulators capable of exchanging forces with the environment. One such application is the installation and...