Abstract We consider the problem of learning level set for which a noisy black-box function exceeds given threshold. To efficiently reconstruct set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic simulators, in particular with heavy-tailed simulation noise and low signal-to-noise ratio. guard against misspecification, assess performance three variants: (i) ...

High-dimensional optimization is a critical challenge for operating large-scale scientific facilities. We apply physics-informed Gaussian process (GP) optimizer to tune complex system by conducting efficient global search. Typical GP models learn from past observations make predictions, but this reduces their applicability new systems where archive data not available. Instead, here we use fast ...

In this article, we develop a new Rao-Blackwellized Monte Carlo smoothing algorithm for conditionally linear Gaussian models. The algorithm is based on the forwardfiltering backward-simulation Monte Carlo smoother concept and performs the backward simulation directly in the marginal space of the non-Gaussian state component while treating the linear part analytically. Unlike the previously prop...

Antimony ores were extracted and processed near the village of Milešov (Příbram district) for about twenty years in second halfof 19th century. Large heaps a small sludge pond left behind after this period. In 1988, locality was inspected andsampled order to gather information residual resources gold antimony. The original archive data from surveywere now studied again interpreted using modern ...

We present a method for obtaining efficient probabilistic solutions to geostatistical and linear inverse problems in spherical geometry. Our Spherical Direct Sequential Simulation (SDSSIM) framework combines information from possibly noisy observations, that provide either point on the model or are related by averaging kernel, statistics derived a-priori information. It generates realizations m...

Langevin equation for a nano-particle suspended in a laminar fluid flow was analytically studied. The Brownian motion generated from molecular bombardment was taken as a Wiener stochastic process and approximated by a Gaussian white noise. Euler-Maruyama method was used to solve the Langevin equation numerically. The accuracy of Brownian simulation was checked by performing a series of simulati...