2021

Articles

Kabanov, D. I., Espath, L., Kiessling, J., & Tempone, R. F. (2021). Estimating divergence-free flows via neural networks. PAMM, 21(1). doi:10.1002/pamm.202100173

Kiessling, J., Ström, E., & Tempone, R. (2021). Wind field reconstruction with adaptive random Fourier features. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 477(2255). doi:10.1098/rspa.2021.0236

Keywords: Random Fourier features, Metropolis algorithm, spatial interpolation, machine learning, wind field reconstruction, flow field estimation

Rached, N. B., Haji-Ali, A.-L., Rubino, G., & Tempone, R. (2021). Efficient importance sampling for large sums of independent and identically distributed random variables. Statistics and Computing, 31(6). doi:10.1007/s11222-021-10055-1

Keywords: Importance sampling, Rare event, Exponential twisting, Gamma IS PDF

Espath, L., Kabanov, D., Kiessling, J., & Tempone, R. (2021). Statistical learning for fluid flows: Sparse Fourier divergence-free approximations. Physics of Fluids, 33(9), 097108. doi:10.1063/5.0064862

Latz, J., Madrigal-Cianci, J. P., Nobile, F., & Tempone, R. (2021). Generalized parallel tempering on Bayesian inverse problems. Statistics and Computing, 31(5). doi:10.1007/s11222-021-10042-6

Keywords: Bayesian inversion, Parallel tempering, Infinites wapping, Markov chain Monte Carlo, Uncertainty quantification

Caballero, R., Kebaier, A., Scavino, M., & Tempone, R. (2021). Quantifying uncertainty with a derivative tracking SDE model and application to wind power forecast data. Statistics and Computing, 31(5). doi:10.1007/s11222-021-10040-8

Keywords: Uncertainty quantification, Forecasting error, Time-inhomogeneous Jacobi diffusion, Lamperti space, Fixed-point likelihood numerical optimization, Model selection, Wind power

Castrillón-Candás, J. E., Nobile, F., & Tempone, R. (2021). A hybrid collocation-perturbation approach for PDEs with random domains. Advances in Computational Mathematics, 47(3). doi:10.1007/s10444-021-09859-6

Keywords: Uncertainty quantification, Stochastic collocation, Perturbat, Stochastic PDEs, Finite elements, Complex analysis, Smolyak sparse grids

Litvinenko, A., Yucel, A., Bagci, H., Oppelstrup, J., Michielssen, E., & Tempone, R. (2021). MLMC method to estimate propagation of uncertainties in electromagnetic fields scattered from objects of uncertain shapes. PAMM, 20(1). doi:10.1002/pamm.202000064

Manuscripts

Bayer, C., Hammouda, C. B., & Tempone, R. Numerical Smoothing with Hierarchical Adaptive Sparse Grids and Quasi-Monte Carlo Methods for Efficient Option Pricing. arXiv preprint, arXiv:2111.01874, 2021

Keywords: Adaptive sparse grid quadrature, Quasi-Monte Carlo, Numerical smoothing, Brownian bridge, Richardson extrapolation, Option pricing, Monte Carlo

Hammouda, C. B., Rached, N. B., Tempone, R., & Wiechert, S. Optimal Importance Sampling via Stochastic Optimal Control for Stochastic Reaction Networks. arXiv preprint, arXiv:2110.14335, 2021

Keywords: Stochastic reaction networks, Monte Carlo, Explicit Tau-Leap scheme, Importance sampling, Stochastic optimal control, Variance reduction, Computational complexity, Neural network, Stochastic optimization

Espath, L., Krumscheid, S., Tempone, R., & Vilanova, P. On the equivalence of different adaptive batch size selection strategies for stochastic gradient descent methods. arXiv preprint, arXiv:2109.10933, 2021

Hoang, T.-V., Krumscheid, S., Hermann, S., & Tempone, R. Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation. arXiv preprint, arXiv:2106.07908, 2021

Keywords: Artificial neural network, Nonlinear filter, Inverse problem, Conditional expectation, Weather forecast

Madrigal-Cianci, J. P., Nobile, F., & Tempone, R. Analysis of a class of Multi-Level Markov Chain Monte Carlo algorithms based on Independent Metropolis-Hastings. arXiv preprint, arXiv:2105.02035, 2021

Keywords: Bayesian inversion; Multi-level Monte Carlo; Markov chain Monte Carlo; Uncertainty quantification

Hoel, H., Shaimerdenova, G., & Tempone, R. Multi-index ensemble Kalman filtering. arXiv preprint, arXiv:2104.07263, 2021

Keywords: Monte Carlo, Multilevel, Multi-index, Convergence rates, Kalman filter, Ensemble Kalman filter

Haji-Ali, A.-L., Hoel, H., & Tempone, R. A simple approach to proving the existence, uniqueness, and strong and weak convergence rates for a broad class of McKean--Vlasov equations. arXiv preprint arXiv:2101.00886, 2021

Keywords: Interacting stochastic particle systems, Stochastic mean-field limit, Weak and strong convergence rates.

2021

Share

Stochastic Numerics Research Group (STOCHNUM)