822 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ReadingGB12 papers
- California Institute of TechnologyUS8 papers
- Fermi National Accelerator LaboratoryUS6 papers
- University of LeicesterGB6 papers
- Columbia UniversityUS5 papers
- Princeton UniversityUS5 papers
- Stanford UniversityUS5 papers
- University College LondonGB5 papers
- Utrecht UniversityNL5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Institute for High Energy PhysicsES4 papers
- Kavli Institute for the Physics and Mathematics of the UniverseJP4 papers
31 papers
Process-Guided Concept Bottleneck Model
Reza M. Asiyabi, SEOSAW Partnership, Steven Hancock +1
Concept Bottleneck Models (CBMs) improve the explainability of black-box Deep Learning (DL) by introducing intermediate semantic concepts. However, standard CBMs often overlook dom…
Homogeneous soil moisture fields suppress Sahelian MCS frequency
Ben Maybee, Cornelia Klein, Christopher M. Taylor +2
Understanding controls on Mesoscale Convective Systems (MCSs) is critical for predicting rainfall extremes across scales. Spatial variability of soil moisture (SM) presents such a…
Estimating carbon pools in the European Shelf sea environment: replacing reanalysis by model-informed machine learning?
Jozef Skakala
Shelf seas are important for the economy and the carbon cycle, but shelf sea observations for carbon pools are often sparse, or highly uncertain. An alternative can be provided by…
Assimilation of machine learning-predicted nitrate to improve the quality of phytoplankton forecasting in the shelf sea environment
Deep S Banerjee, Jozef Skakala, David Ford
We demonstrate that assimilating Neural Network (NN)-predicted surface nitrate leads to a major improvement in phytoplankton short-range (1-5 day) dynamical model forecasts for the…
Hybrid machine learning data assimilation for marine biogeochemistry
Ieuan Higgs, Ross Bannister, Jozef Skákala +2
Marine biogeochemistry models are critical for forecasting, as well as estimating ecosystem responses to climate change and human activities. Data assimilation (DA) improves these…
The Atacama Cosmology Telescope: DR6 Maps
Sigurd Naess, Yilun Guan, Adriaan J. Duivenvoorden +163
We present Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) maps of the Cosmic Microwave Background temperature and polarization anisotropy at arcminute resolution over three…
Improving Oil Slick Trajectory Simulations with Bayesian Optimization
Gabriele Accarino, Marco M. De Carlo, Igor Atake +8
Accurate simulations of oil spill trajectories are essential for supporting practitioners' response and mitigating environmental and socioeconomic impacts. Numerical models, such a…
The Atacama Cosmology Telescope: DR6 Constraints on Extended Cosmological Models
Erminia Calabrese, J. Colin Hill, Hidde T. Jense +169
We use new cosmic microwave background (CMB) primary temperature and polarization anisotropy measurements from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) to test fo…
Studying baryon acoustic oscillations using photometric redshifts from the DESI Legacy Imaging survey DR9
Christoph Saulder, Yong-Seon Song, Minji Oh +41
Context.The Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Survey DR9 (DR9 hereafter), with its extensive dataset of galaxy locations and photometric redshifts, present…
Nesterov Acceleration for Ensemble Kalman Inversion and Variants
Sydney Vernon, Eviatar Bach, Oliver R. A. Dunbar
Ensemble Kalman inversion (EKI) is a derivative-free, particle-based optimization method for solving inverse problems. It can be shown that EKI approximates a gradient flow, which…
Dark Energy Survey Year 6 Results: Point-spread Function Modeling
T. Schutt, M. Jarvis, A. Roodman +70
We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimatio…
Forecast error growth: A dynamic-stochastic model
Eviatar Bach, Dan Crisan, Michael Ghil
There is a history of simple forecast error growth models designed to capture the key properties of error growth in operational numerical weather prediction (NWP) models. We propos…
Dark photon constraints from CMB temperature anisotropies
Andres Aramburo-Garcia, Kyrylo Bondarenko, Alexey Boyarsky +6
The resonant conversion, within the inter-galactic medium, of regular photons into dark photons amplifies the anisotropy observed in the CMB, thereby imposing stringent constraints…
Broadband Multi-wavelength Properties of M87 during the 2018 EHT Campaign including a Very High Energy Flaring Episode
J. C. Algaba, M. Balokovic, S. Chandra +738
The nearby elliptical galaxy M87 contains one of the only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (…
Opening the Black-Box: A Systematic Review on Explainable AI in Remote Sensing
Adrian Höhl, Ivica Obadic, Miguel Ángel Fernández Torres +5
In recent years, black-box machine learning approaches have become a dominant modeling paradigm for knowledge extraction in remote sensing. Despite the potential benefits of uncove…
Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents
Daniel Ayers, Jack Lau, Javier Amezcua +2
In chaotic dynamical systems such as the weather, prediction errors grow faster in some situations than in others. Real-time knowledge about the error growth could enable strategie…
Disentangling the neighbouring pulsars SXP 15.3 and SXP 305
Itumeleng M. Monageng, Malcolm J. Coe, Lee J. Townsend +8
SXP 15.3 and SXP 305 are two Be X-ray binaries in the Small Magellanic Cloud that are spatially separated by ~7 arcsec. The small separation between these sources has, in the past,…
On time-parallel preconditioning for the state formulation of incremental weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
Using a high degree of parallelism is essential to perform data assimilation efficiently. The state formulation of the incremental weak constraint four-dimensional variational data…
Randomised preconditioning for the forcing formulation of weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
There is growing awareness that errors in the model equations cannot be ignored in data assimilation methods such as four-dimensional variational assimilation (4D-Var). If allowed…
Quantifying vegetation biophysical variables from imaging spectroscopy data: a review on retrieval methods
Jochem Verrelst, Zbyněk Malenovský, Christiaan Van der Tol +5
An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream…
New bounds on the condition number of the Hessian of the preconditioned variational data assimilation problem
Jemima M. Tabeart, Sarah L. Dance, Amos S. Lawless +2
Data assimilation algorithms combine prior and observational information, weighted by their respective uncertainties, to obtain the most likely posterior of a dynamical system. In…
Ensemble Kalman Filter for non-conservative moving mesh solvers with a joint physics and mesh location update
Christian Sampson, Alberto Carrassi, Ali Aydoğdu +1
Numerical solvers using adaptive meshes can focus computational power on important regions of a model domain capturing important or unresolved physics. The adaptation can be inform…
Low complexity model to study scale dependence of phytoplankton dynamics in the tropical Pacific
Jozef Skakala, Paolo Lazzari
We demonstrate that a simple model based on reaction-diffusion-advection (RDA) equation forced by realistic surface velocities and nutrients is skilled in reproducing the distribut…
Assimilation of atmospheric infrasound data to constrain tropospheric and stratospheric winds
Javier Amezcua, Sven Peter Näsholm, Erik Mårten Blixt +1
This data assimilation study exploits infrasound from explosions to probe an atmospheric wind component from the ground up to stratospheric altitudes. Planned explosions of old amm…