Image de couverture de livre

Surface temperature extremes produced by huge machine learning hindcasts of summer 2023

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Risser, Mark, Mahesh, Ankur, North, Joshua, Collins, William D., Bonev, Boris, Kashinath, Karthik, Kurth, Thorsten, Subramanian, Shashank, Pritchard, Michael S.
Format:	Preprint
Publié:	2026
Sujets:	Applications
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
par: Bonev, Boris, et autres
Publié: (2025)

Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators
par: Mahesh, Ankur, et autres
Publié: (2024)

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators
par: Mahesh, Ankur, et autres
Publié: (2024)

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators
par: Mahesh, Ankur, et autres
Publié: (2026)

Validity in machine learning for extreme event attribution
par: Chou, Cassandra C., et autres
Publié: (2025)

Using spatial extreme-value theory with machine learning to model and understand spatially compounding weather extremes
par: Koh, Jonathan, et autres
Publié: (2024)

Stability of clinical prediction models developed using statistical or machine learning methods
par: Riley, Richard D, et autres
Publié: (2022)

Granger causal inference for climate change attribution
par: Risser, Mark D., et autres
Publié: (2024)

A Practical Probabilistic Benchmark for AI Weather Models
par: Brenowitz, Noah D., et autres
Publié: (2024)

Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecasts
par: Leinonen, Jussi, et autres
Publié: (2024)

Predictive Hotspot Mapping for Data-driven Crime Prediction
par: Sriram, Karthik, et autres
Publié: (2026)

Optimal day-ahead offering strategy for large producers based on market price response learning
par: Alcántara, António, et autres
Publié: (2022)

Traffic noise assessment in urban Bulgaria using explainable machine learning
par: Helbic, Marco, et autres
Publié: (2025)

The contribution of machine learning to the prevention of burnout among healthcare workers in Morocco
par: Eddaou, Mohammed
Publié: (2025)

Explaining the unexplainable: leveraging extremal dependence to characterize the 2021 Pacific Northwest heatwave
par: Zhang, Likun, et autres
Publié: (2023)

A causal machine learning approach to disentangling the pressure-satisfaction pathways in depression
par: Nan, Zhaojin
Publié: (2025)

Private and Collaborative Kaplan-Meier Estimators
par: Rahimian, Shadi, et autres
Publié: (2023)

Causal machine learning for predicting treatment outcomes
par: Feuerriegel, Stefan, et autres
Publié: (2024)

Double machine learning to estimate the effects of multiple treatments and their interactions
par: Xiang, Qingyan, et autres
Publié: (2025)

Assessing variable importance in survival analysis using machine learning
par: Wolock, Charles J., et autres
Publié: (2023)

Identification of socioeconomic factors influencing global food price security using machine learning
par: Shan, Shan
Publié: (2024)

Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
par: Risser, Mark D., et autres
Publié: (2024)

Analysis of points outcome in ATP Grand Slam Tennis using big data and machine learning
par: Illum, Martin, et autres
Publié: (2025)

Towards accurate extreme event likelihoods from diffusion model climate emulators
par: Manshausen, Peter, et autres
Publié: (2026)

Biarchetype analysis: simultaneous learning of observations and features based on extremes
par: Alcacer, Aleix, et autres
Publié: (2023)

Stochastic modeling of particle structures in spray fluidized bed agglomeration using methods from machine learning
par: Fuchs, Lukas, et autres
Publié: (2025)

Certification of MPC-based zonal controller security properties using accuracy-aware machine learning proxies
par: Houdouin, Pierre, et autres
Publié: (2024)

Probabilistic storyline attribution using machine learning
par: Loer, Frieder, et autres
Publié: (2026)

Applications of machine learning to predict seasonal precipitation for East Africa
par: Scheuerer, Michael, et autres
Publié: (2024)

Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data
par: Bouvier, Florie, et autres
Publié: (2023)

Waiting for Dabo: A machine learning model for predicting Power 4 college football coaching hire success
par: Schuckers, Michael, et autres
Publié: (2025)

Precrop Payoffs: Causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets
par: Kluger, Dan M., et autres
Publié: (2025)

Modeling zero-inflated precipitation extremes
par: Abbas, Aamar, et autres
Publié: (2025)

Probabilistic forecasting of weather-driven faults in electricity networks: a flexible approach for extreme and non-extreme events
par: Maia, Mateus, et autres
Publié: (2026)

Accounting for variable detection functions in temporal abundance modeling via transfer learning
par: Collins, Kevin M., et autres
Publié: (2026)

Logarithmic resilience risk metrics that address the huge variations in blackout cost
par: Ahmad, Arslan, et autres
Publié: (2025)

Probabilistic intraday electricity price forecasting using generative machine learning
par: Chen, Jieyu, et autres
Publié: (2025)

Error-controlled non-additive interaction discovery in machine learning models
par: Chen, Winston, et autres
Publié: (2024)

Are machine learning interpretations reliable? A stability study on global interpretations
par: Gan, Luqin, et autres
Publié: (2025)

A random forest machine learning model to detect fluvial hazards
par: Marco Gava, et autres
Publié: (2024)