76 citations · 424 across the 28 of their papers we have counts for
29 papers
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
Stochastic Processes with Modified Lognormal Distribution Featuring Flexible Upper Tail
Dionissios T. Hristopulos, Anastassia Baxevani, Giorgio Kaniadakis
Asymmetric, non-Gaussian probability distributions are often observed in the analysis of natural and engineering datasets. The lognormal distribution is a standard model for data w…
Information Flow Rate for Cross-Correlated Stochastic Processes
Dionissios T. Hristopulos
Causal inference seeks to identify cause-and-effect interactions in coupled systems. A recently proposed method by Liang detects causal relations by quantifying the direction and m…
A parsimonious, computationally efficient machine learning method for spatial regression
Milan Žukovič, Dionissios T. Hristopulos
We introduce the modified planar rotator method (MPRS), a physically inspired machine learning method for spatial/temporal regression. MPRS is a non-parametric model which incorpor…
Non-separable Covariance Kernels for Spatiotemporal Gaussian Processes based on a Hybrid Spectral Method and the Harmonic Oscillator
Dionissios T. Hristopulos
Gaussian processes provide a flexible, non-parametric framework for the approximation of functions in high-dimensional spaces. The covariance kernel is the main engine of Gaussian…
Spatial data modeling by means of Gibbs Markov random fields based on a generalized planar rotator model
Milan Žukovič, Dionissios T. Hristopulos
We introduce a Gibbs Markov random field for spatial data on Cartesian grids which is based on the generalized planar rotator (GPR) model. The GPR model generalizes the recently pr…
Boltzmann-Gibbs Random Fields with Mesh-free Precision Operators Based on Smoothed Particle Hydrodynamics
Dionissios T. Hristopulos
Boltzmann-Gibbs random fields are defined in terms of the exponential expression exp(-H), where H is a suitably defined energy functional of the field states x(s). This paper prese…
Non-parametric Kernel-Based Estimation of Probability Distributions for Precipitation Modeling
Andrew Pavlides, Vasiliki Agou, Dionissios T. Hristopulos
The probability distribution of precipitation amount strongly depends on geography, climate zone, and time scale considered. Closed-form parametric probability distributions are no…
The k-statistics approach to epidemiology
Giorgio Kaniadakis, Mauro M. Baldi, Thomas S. Deisboeck +6
A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while…
Stochastic Local Interaction Model: Geostatistics without Kriging
Dionissios T. Hristopulos, Andreas Pavlides, Vasiliki D. Agou +1
Classical geostatistical methods face serious computational challenges if they are confronted with large sets of spatially distributed data. We present a simplified stochastic loca…
Efficient and Scalable Approach to Equilibrium Conditional Simulation of Gibbs Markov Random Fields
Milan Žukovič, Dionissios T. Hristopulos
We study the performance of an automated hybrid Monte Carlo (HMC) approach for conditional simulation of a recently proposed, single-parameter Gibbs Markov random field (Gibbs MRF)…
Stochastic Local Interaction Model with Sparse Precision Matrix for Space-Time Interpolation
Dionissios T. Hristopulos, Vasiliki D. Agou
The application of geostatistical and machine learning methods based on Gaussian processes to big space-time data is beset by the requirement for storing and numerically inverting…
GPU-accelerated Simulation of Massive Spatial Data based on the Modified Planar Rotator Model
Milan Žukovič, Michal Borovský, Matúš Lach +1
A novel Gibbs Markov random field for spatial data on Cartesian grids based on the modified planar rotator (MPR) model of statistical physics has been recently introduced for effic…
Nonlinear Kinetics on Lattices based on the Kinetic Interaction Principle
Giorgio Kaniadakis, Dionissios T. Hristopulos
Master equations define the dynamics that govern the time evolution of various physical processes on lattices. In the continuum limit, master equations lead to Fokker-Planck partia…
Gibbs Markov Random Fields with Continuous Values based on the Modified Planar Rotator Model
Milan Žukovič, Dionissios T. Hristopulos
We introduce a novel Gibbs Markov random field for spatial data on Cartesian grids based on the modified planar rotator (MPR) model of statistical physics. The MPR captures spatial…
Space-Time Covariance Functions based on Linear Response Theory and the Turning Bands Method
Dionissios T. Hristopulos, Ivi C. Tsantili
The generation of non-separable, physically motivated covariance functions is a theme of ongoing research interest, given that only a few classes of such functions are available. W…
Space-Time Models based on Random Fields with Local Interactions
Dionissios T. Hristopulos, Ivi C. Tsantili
The analysis of space-time data from complex, real-life phenomena requires the use of flexible and physically motivated covariance functions. In most cases, it is not possible to e…
Stochastic Local Interaction (SLI) Model: Interfacing Machine Learning and Geostatistics
Dionissios T. Hristopulos
Machine learning and geostatistics are powerful mathematical frameworks for modeling spatial data. Both approaches, however, suffer from poor scaling of the required computational…
Kinetic Model of Mass Exchange with Dynamic Arrhenius Transition Rates
Dionissios T. Hristopulos, Aliki D. Muradova
We study a nonlinear kinetic model of mass exchange between interacting grains. The transition rates follow the Arrhenius equation with an activation energy that depends on the gra…
Radial Covariance Functions Motivated by Spatial Random Field Models with Local Interactions
Dionissios T. Hristopulos
We derive explicit expressions for a family of radially symmetric, non-differentiable, Spartan covariance functions in that involve the modified Bessel function of t…
Finite-Size Effects on Return Interval Distributions for Weakest-Link-Scaling Systems
Dionissios T. Hristopulos, Manolis P. Petrakis, Giorgio Kaniadakis
The Weibull distribution is a commonly used model for the strength of brittle materials and earthquake return intervals. Deviations from Weibull scaling, however, have been observe…
A Directional Gradient-Curvature Method for Gap Filling of Gridded Environmental Spatial Data with Potentially Anisotropic Correlations
Milan Žukovič, Dionissios T. Hristopulos
We introduce the Directional Gradient-Curvature (DGC) method, a novel approach for filling gaps in gridded environmental data. DGC is based on an objective function that measures t…
Classification of missing values in spatial data using spin models
Milan Žukovič, Dionissios T. Hristopulos
A problem of current interest is the estimation of spatially distributed processes at locations where measurements are missing. Linear interpolation methods rely on the Gaussian as…
Non-Parametric Approximations for Anisotropy Estimation in Two-dimensional Differentiable Gaussian Random Fields
Manolis P. Petrakis, Dionissios T. Hristopulos
Spatially referenced data often have autocovariance functions with elliptical isolevel contours, a property known as geometric anisotropy. The anisotropy parameters include the til…