Copertina

Bayesian Optimisation for Active Monitoring of Air Pollution

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hellan, Sigrid Passano, Lucas, Christopher G., Goddard, Nigel H.
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Machine Learning Atmospheric and Oceanic Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Data-driven Prior Learning for Bayesian Optimisation
di: Hellan, Sigrid Passano, et al.
Pubblicazione: (2023)

Bayesian Optimisation Against Climate Change: Applications and Benchmarks
di: Hellan, Sigrid Passano, et al.
Pubblicazione: (2023)

Difference Learning for Air Quality Forecasting Transport Emulation
di: Chen, Reed River, et al.
Pubblicazione: (2024)

Causal Links Between Anthropogenic Emissions and Air Pollution Dynamics in Delhi
di: Das, Sourish, et al.
Pubblicazione: (2025)

Training-Free Bayesian Filtering with Generative Emulators
di: Savary, Thomas, et al.
Pubblicazione: (2026)

Probabilistic Joint Recovery Method for CO$_2$ Plume Monitoring
di: Deng, Zijun, et al.
Pubblicazione: (2025)

CAAL: Confidence-Aware Active Learning for Heteroscedastic Atmospheric Regression
di: Jiang, Fei, et al.
Pubblicazione: (2026)

AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion
di: Luitel, Somnath, et al.
Pubblicazione: (2026)

Machine Learning Framework for High-Resolution Air Temperature Downscaling Using LiDAR-Derived Urban Morphological Features
di: Chajaei, Fatemeh, et al.
Pubblicazione: (2024)

Simulating the Air Quality Impact of Prescribed Fires Using Graph Neural Network-Based PM$_{2.5}$ Forecasts
di: Liao, Kyleen, et al.
Pubblicazione: (2023)

Efficient fine-tuning of 37-level GraphCast with the Canadian global deterministic analysis
di: Subich, Christopher
Pubblicazione: (2024)

AODDiff: Probabilistic Reconstruction of Aerosol Optical Depth via Diffusion-based Bayesian Inference
di: Fan, Linhao, et al.
Pubblicazione: (2025)

Acceleration of horizontal numerical advection for atmospheric modeling through surrogate modeling with temporal coarse-graining
di: Park, Manho, et al.
Pubblicazione: (2026)

Ensemble-size-dependence of deep-learning post-processing methods that minimize an (un)fair score: motivating examples and a proof-of-concept solution
di: Roberts, Christopher David
Pubblicazione: (2026)

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators
di: Mahesh, Ankur, et al.
Pubblicazione: (2026)

ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses
di: Watt-Meyer, Oliver, et al.
Pubblicazione: (2024)

Data-Driven Probabilistic Air-Sea Flux Parameterization
di: Wu, Jiarong, et al.
Pubblicazione: (2025)

Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning
di: Howard, Lucas, et al.
Pubblicazione: (2025)

Effective Benchmarks for Optical Turbulence Modeling
di: Jellen, Christopher, et al.
Pubblicazione: (2024)

Utilizing Low-Cost Sensors to Monitor Indoor Air Quality in Mongolian Gers
di: Flowerday, Callum E., et al.
Pubblicazione: (2024)

DeepSeasons: a Deep Learning scale-selecting approach to Seasonal Forecasts
di: Navarra, A., et al.
Pubblicazione: (2025)

Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
di: Tian, Jindong, et al.
Pubblicazione: (2024)

Physics Guided Machine Learning Methods for Hydrology
di: Khandelwal, Ankush, et al.
Pubblicazione: (2020)

Emulation with uncertainty quantification of regional sea-level change caused by the Antarctic Ice Sheet
di: Yoo, Myungsoo, et al.
Pubblicazione: (2024)

An AI-driven framework for the prediction of personalised health response to air pollution
di: Zounemat-Kermani, Nazanin, et al.
Pubblicazione: (2025)

Machine learning models for daily rainfall forecasting in Northern Tropical Africa using tropical wave predictors
di: Satheesh, Athul Rasheeda, et al.
Pubblicazione: (2024)

Identifying Three-Dimensional Radiative Patterns Associated with Early Tropical Cyclone Intensification
di: Tam, Frederick Iat-Hin, et al.
Pubblicazione: (2024)

Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting
di: Pereira, Carlos A., et al.
Pubblicazione: (2026)

Data-driven Seasonal Climate Predictions via Variational Inference and Transformers
di: Palma, Lluís, et al.
Pubblicazione: (2025)

Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging
di: Husain, Syed Zahid, et al.
Pubblicazione: (2024)

CloudSense: A Model for Cloud Type Identification using Machine Learning from Radar data
di: Nizar, Mehzooz, et al.
Pubblicazione: (2024)

Generative Modeling of Aerosol State Representations
di: Saleh, Ehsan, et al.
Pubblicazione: (2025)

M-CaStLe: Uncovering Local Causal Structures in Multivariate Space-Time Gridded Data
di: Nichol, J. Jake, et al.
Pubblicazione: (2026)

SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
di: Duncan, James P. C., et al.
Pubblicazione: (2025)

Prithvi WxC: Foundation Model for Weather and Climate
di: Schmude, Johannes, et al.
Pubblicazione: (2024)

ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
di: Yu, Sungduk, et al.
Pubblicazione: (2023)

Uncertainty quantification for data-driven weather models
di: Bülte, Christopher, et al.
Pubblicazione: (2024)

Urban Air Pollution Forecasting: a Machine Learning Approach leveraging Satellite Observations and Meteorological Forecasts
di: Blanco, Giacomo, et al.
Pubblicazione: (2024)

FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design
di: Dunstan, Tom, et al.
Pubblicazione: (2025)

Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
di: Orlova, Elena, et al.
Pubblicazione: (2022)