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Self-exciting spatio-temporal point process models predict the rate of events as a function of space, time, and the previous history of events. These models naturally capture triggering and clustering behavior, and have been widely used in…

Methodology · Statistics 2018-08-14 Alex Reinhart

Spatiotemporal dynamics models are fundamental for various domains, from heat propagation in materials to oceanic and atmospheric flows. However, currently available neural network-based spatiotemporal modeling approaches fall short when…

Machine Learning · Computer Science 2025-02-11 Valerii Iakovlev , Harri Lähdesmäki

Spatio-temporal problems exist in many areas of knowledge and disciplines ranging from biology to engineering and physics. However, solution strategies based on classical statistical techniques often fall short due to the large number of…

Applications · Statistics 2017-06-15 Emil B. Iversen , Rune Juhl , Jan K. Møller , Jan Kleissl , Henrik Madsen , Juan M. Morales

The rapid growth of solar energy is reshaping power system operations and increasing the complexity of grid management. As photovoltaic (PV) capacity expands, short-term fluctuations in PV generation introduce substantial operational…

Machine Learning · Computer Science 2026-03-30 Luca Lanzilao , Angela Meyer

In recent years there has been a substantial increase in the availability of datasets which contain information about the location and timing of an event or group of events and the application of methods to analyse spatio-temporal datasets…

Methodology · Statistics 2019-10-02 Nik Lomax , Nick Malleson , Le-Minh Kieu

The capability to predict the parameters of an SEP event such as its onset, peak flux, and duration is critical to assessing any potential space weather impact. We present a new flexible modelling system simulating the propagation of Solar…

Solar and Stellar Astrophysics · Physics 2015-06-01 M. S. Marsh , S. Dalla , M. Dierckxsens , T. Laitinen , N. B. Crosby

Solar energetic particle (SEP) events, as one of the most prominent manifestations of solar activity, can generate severe hazardous radiation when accelerated by solar flares or shock waves formed aside from coronal mass ejections (CMEs).…

Machine Learning · Computer Science 2025-11-13 Anli Ji , Pranjal Patil , Chetraj Pandey , Manolis K. Georgoulis , Berkay Aydin

Global and regional climate model projections are useful for gauging future patterns of climate variables, including solar radiation, but data from these models is often too coarse to assess local impacts. Within the context of solar…

Applications · Statistics 2024-05-21 Maggie Bailey , Doug Nychka , Manajit Sengupta , Jaemo Yang , Soutir Bandyopadhyay

In the probabilistic energy forecasting literature, emphasis is mainly placed on deriving marginal predictive densities for which each random variable is dealt with individually. Such marginals description is sufficient for power systems…

Applications · Statistics 2016-03-23 Faranak Golestaneh , Pierre Pinson , Hoay Beng Gooi

Electricity is difficult to store, except at prohibitive cost, and therefore the balance between generation and load must be maintained at all times. Electricity is traditionally managed by anticipating demand and intermittent production…

Machine Learning · Computer Science 2024-09-26 Julie Keisler , Margaux Bregere

Extreme weather is one of the main mechanisms through which climate change will directly impact human society. Coping with such change as a global community requires markedly improved understanding of how global warming drives extreme…

Computational Physics · Physics 2019-09-18 Adam Rupe , Karthik Kashinath , Nalini Kumar , Victor Lee , Prabhat , James P. Crutchfield

Prediction of the Solar Energetic Particle (SEP) events garner increasing interest as space missions extend beyond Earth's protective magnetosphere. These events, which are, in most cases, products of magnetic reconnection-driven processes…

The prediction of solar flares, eruptions, and high energy particle storms is of great societal importance. The data mining approach to forecasting has been shown to be very promising. Benchmark datasets are a key element in the further…

Solar and Stellar Astrophysics · Physics 2018-08-22 Petrus C. Martens , Rafal A. Angryk

Space weather events may cause damage to several fields, including aviation, satellites, oil and gas industries, and electrical systems, leading to economic and commercial losses. Solar flares are one of the most significant events, and…

Solar and Stellar Astrophysics · Physics 2020-06-25 T. Cinto , A. L. S. Gradvohl , G. P. Coelho , A. E. A. da Silva

Record-breaking temperature events are now very frequently in the news, viewed as evidence of climate change. With this as motivation, we undertake the first substantial spatial modeling investigation of temperature record-breaking across…

Modeling of transient events in the solar atmosphere requires the confluence of 3 critical elements: (1) model sophistication, (2) data availability, and (3) data assimilation. This white paper describes required advances that will enable…

Instrumentation and Methods for Astrophysics · Physics 2023-01-02 M. Rempel , Y. Fan , M. Dikpati , A. Malanushenko , M. D. Kazachenko , M. C. M. Cheung , G. Chintzoglou , X. Sun , G. H. Fisher , T. Y. Chen

Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions. Nonetheless, the inherent variability of solar irradiance poses a significant challenge for seamlessly integrating solar power…

Machine Learning · Computer Science 2023-10-24 Oussama Boussif , Ghait Boukachab , Dan Assouline , Stefano Massaroli , Tianle Yuan , Loubna Benabbou , Yoshua Bengio

Solar Energetic Particles (SEPs) are an important aspect of space weather. SEP events posses a high destructive potential, since they may cause disruptions of communication systems on Earth and be fatal to crew members onboard spacecrafts…

Space Physics · Physics 2018-09-05 D. Borovikov , I. V. Sokolov , I. Roussev , A. Taktakishvili , T. I. Gombosi

In real-world scenario, many phenomena produce a collection of events that occur in continuous time. Point Processes provide a natural mathematical framework for modeling these sequences of events. In this survey, we investigate…

We consider multi-task regression models where the observations are assumed to be a linear combination of several latent node functions and weight functions, which are both drawn from Gaussian process priors. Driven by the problem of…

Machine Learning · Statistics 2018-12-05 Astrid Dahl , Edwin V. Bonilla
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