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Flow and diffusion models are typically pre-trained on limited available data (e.g., molecular samples), covering only a fraction of the valid design space (e.g., the full molecular space). As a consequence, they tend to generate samples…

Machine Learning · Computer Science 2026-02-19 Riccardo De Santi , Kimon Protopapas , Ya-Ping Hsieh , Andreas Krause

The paper presents experiments of driving a physics-based thermosphere model by assimilating electron density (Ne) and temperature (Tn) data using the ensemble adjustment Kalman filter (EAKF) technique. This study not only helps to gauge…

Space Physics · Physics 2019-03-22 Timothy Kodikara , Kefei Zhang

Extreme Precipitation Events (EPEs) can have devastating consequences such as floods and landslides, posing a great threat to society and the economy. Predicting such events long in advance can support the mitigation of negative impacts.…

Atmospheric and Oceanic Physics · Physics 2022-03-14 Nikolaos Mastrantonas , Linus Magnusson , Florian Pappenberger , Jörg Matschullat

Turbulent mixing exerts a significant influence on many physical processes in the ocean. In a stably stratified Boussinesq fluid, this irreversible mixing describes the conversion of available potential energy (APE) to background potential…

Fluid Dynamics · Physics 2021-03-18 Christopher J. Howland , John R. Taylor , C. P. Caulfield

Forecast models in statistical seismology are commonly evaluated with log-likelihood scores of the full distribution P(n) of earthquake numbers, yet heavy tails and out-of-range observations can bias model ranking. We develop a tail-aware…

Geophysics · Physics 2026-02-24 Jiawei Li , Qingyuan Zhang , Didier Sornette

Energy forecasting is vital for grid reliability and operational efficiency. Although recent advances in time series forecasting have led to progress, existing benchmarks remain limited in spatial and temporal scope and lack multi-energy…

Machine Learning · Computer Science 2025-09-09 Chen Shao , Yue Wang , Zhenyi Zhu , Zhanbo Huang , Sebastian Pütz , Benjamin Schäfer , Tobais Käfer , Michael Färber

We study an option pricing framework that accounts for the price impact of an earnings announcement (EA), and analyze the behavior of the implied volatility surface prior to the event. On the announcement date, we incorporate a random jump…

Pricing of Securities · Quantitative Finance 2015-04-09 Tim Leung , Marco Santoli

We present the Empirical Dust Attenuation (EDA) framework -- a flexible prescription for assigning realistic dust attenuation to simulated galaxies based on their physical properties. We use the EDA to forward model synthetic observations…

Subsurface storage of CO$_2$ is an important means to mitigate climate change, and to investigate the fate of CO$_2$ over several decades in vast reservoirs, numerical simulation based on realistic models is essential. Faults and other…

Numerical Analysis · Mathematics 2023-12-12 Per Pettersson , Eirik Keilegavlen , Tor Harald Sandve , Sarah Gasda , Sebastian Krumscheid

Buildings rarely perform as designed/simulated and and there are numerous tangible benefits if this gap is reconciled. A new scientific yet pragmatic methodology - called Enhanced Parameter Estimation (EPE) - is proposed that allows…

Systems and Control · Electrical Eng. & Systems 2021-03-15 Kris Subbarao , Srijan Didwania , T. Agami Reddy , Marlin Addison

Estimation of the failure probability of offshore structures exposed to extreme ocean environments is critical to their safe design and operation. The conditional density of the environment (CDE) quantifies regions of the space of long term…

Applications · Statistics 2025-12-16 Matthew Speers , Jonathan Angus Tawn , Philip Jonathan

A numerical tool for analysing spatially anisotropic electron populations in electron cyclotron resonance (ECR) plasmas has been developed, using a trial-and-error electron energy distribution function (EEDF) fitting method. The method has…

Plasma Physics · Physics 2021-10-27 B. Mishra , A. Pidatella , S. Biri , A. Galatà , E. Naselli , R. Rácz , G. Torrisi , D. Mascali

Large scale deep learning model, such as modern language models and diffusion architectures, have revolutionized applications ranging from natural language processing to computer vision. However, their deployment in distributed or…

Testing earthquake forecasts is essential to obtain scientific information on forecasting models and sufficient credibility for societal usage. We aim at enhancing the testing phase proposed by the Collaboratory for the Study of Earthquake…

Applications · Statistics 2026-02-03 Jonas R. Brehmer , Kristof Kraus , Tilmann Gneiting , Marcus Herrmann , Warner Marzocchi

Fragments of deep-ocean tidal records up to 3 days long belong to the same functional sub-space, regardless of the record's origin. The tidal sub-space basis can be derived via Empirical Orthogonal Function (EOF) analysis of a tidal record…

Atmospheric and Oceanic Physics · Physics 2014-04-29 Elena Tolkova

Simulating turbulent fluid flows is a computationally prohibitive task, as it requires the resolution of fine-scale structures and the capture of complex nonlinear interactions across multiple scales. This is particularly the case in direct…

Fluid Dynamics · Physics 2026-04-22 Ismaël Zighed , Nicolas Thome , Patrick Gallinari , Taraneh Sayadi

Many online platforms have deployed anti-fraud systems to detect and prevent fraudulent activities. However, there is usually a gap between the time that a user commits a fraudulent action and the time that the user is suspended by the…

Machine Learning · Computer Science 2018-11-15 Panpan Zheng , Shuhan Yuan , Xintao Wu

Meteotsunamis are atmospherically driven sea-level oscillations that can trigger hazardous coastal flooding, particularly in resonant bays. This study assesses the GPU-based Meteo-HySEA model for meteotsunami simulation in the Adriatic Sea,…

Geophysics · Physics 2026-01-08 Alejandro González , Cléa Denamiel , Jorge Macías

Microearthquakes (MEQs) generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their full spatiotemporal evolution is therefore critical for applications such as enhanced…

Geophysics · Physics 2025-08-05 Jaehong Chung , Michael Manga , Timothy Kneafsey , Tapan Mukerji , Mengsu Hu

Coronal mass ejections (CMEs) and eruptive flares (EFs) are the most energetic explosions in the solar system. Their underlying origin is the free energy that builds up slowly in the sheared magnetic field of a filament channel. We report…

Solar and Stellar Astrophysics · Physics 2019-10-03 Joel T. Dahlin , Spiro K. Antiochos , C. Richard DeVore