Cover Image

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Sibo, Chassagnon, Hector, Kasoar, Matthew, Guo, Yike, Arcucci, Rossella
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explainable Global Wildfire Prediction Models using Graph Neural Networks
by: Chen, Dayou, et al.
Published: (2024)

Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training
by: Qin, Jiuming, et al.
Published: (2024)

Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data
by: Pang, Bo, et al.
Published: (2024)

Multi-fidelity physics constrained neural networks for dynamical systems
by: Zhou, Hao, et al.
Published: (2024)

Knowledge-enhanced Multimodal ECG Representation Learning with Arbitrary-Lead Inputs
by: Liu, Che, et al.
Published: (2025)

TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functions
by: Cheng, Sibo, et al.
Published: (2024)

DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data. A case study over South America
by: Seal, Daniel, et al.
Published: (2024)

Guaranteed prediction sets for functional surrogate models
by: Gray, Ander, et al.
Published: (2025)

Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
by: Liu, Che, et al.
Published: (2024)

Assessment of deep learning models integrated with weather and environmental variables for wildfire spread prediction and a case study of the 2023 Maui fires
by: Kim, Jiyeon, et al.
Published: (2025)

Scaling laws for learning with real and surrogate data
by: Jain, Ayush, et al.
Published: (2024)

SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning
by: Cai, Mingsheng, et al.
Published: (2025)

NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning
by: Ramirez-Sanchez, Edgar, et al.
Published: (2025)

Development of a graph neural network surrogate for travel demand modelling
by: Makarov, Nikita, et al.
Published: (2024)

Deep reinforcement learning with time-scale invariant memory
by: Kabir, Md Rysul, et al.
Published: (2024)

Deep learning with noisy labels in medical prediction problems: a scoping review
by: Wei, Yishu, et al.
Published: (2024)

Building surrogate models using trajectories of agents trained by Reinforcement Learning
by: Cestero, Julen, et al.
Published: (2025)

The surprising efficiency of temporal difference learning for rare event prediction
by: Cheng, Xiaoou, et al.
Published: (2024)

PROTECT: Protein circadian time prediction using unsupervised learning
by: Ogholbake, Aram Ansary, et al.
Published: (2025)

Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks
by: Mei, Taiyuan, et al.
Published: (2024)

A Probabilistic Approach to Wildfire Spread Prediction Using a Denoising Diffusion Surrogate Model
by: Yu, Wenbo, et al.
Published: (2025)

Sample-efficient quantum error mitigation via classical learning surrogates
by: Liao, Wei-You, et al.
Published: (2025)

An adaptive sampling algorithm for data-generation to build a data-manifold for physical problem surrogate modeling
by: Mang, Chetra, et al.
Published: (2025)

Data efficient surrogate modeling for engineering design: Ensemble-free batch mode deep active learning for regression
by: Kapoor, Sarthak, et al.
Published: (2022)

Time-series surrogates from energy consumers generated by machine learning approaches for long-term forecasting scenarios
by: Gerhards, Ben, et al.
Published: (2025)

Evaluating machine learning models for predicting pesticide toxicity to honey bees
by: Adamczyk, Jakub, et al.
Published: (2025)

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning
by: Hutson, Miles, et al.
Published: (2024)

Monitoring fairness in machine learning models that predict patient mortality in the ICU
by: van Schaik, Tempest A., et al.
Published: (2024)

Knowledge-guided generative surrogate modeling for high-dimensional design optimization under scarce data
by: Wang, Bingran, et al.
Published: (2026)

Sparse Adapter Fusion for Continual Learning in NLP
by: Zeng, Min, et al.
Published: (2026)

Characterising harmful data sources when constructing multi-fidelity surrogate models
by: Andrés-Thió, Nicolau, et al.
Published: (2024)

Spatially-Aware Diffusion Models with Cross-Attention for Global Field Reconstruction with Sparse Observations
by: Zhuang, Yilin, et al.
Published: (2024)

G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
by: Liu, Che, et al.
Published: (2023)

Active learning for structural reliability analysis with multiple limit state functions through variance-enhanced PC-Kriging surrogate models
by: A., J. Moran, et al.
Published: (2023)

DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome
by: Dutta, Pratik, et al.
Published: (2025)

Physics-informed self-supervised learning for predictive modeling of coronary artery digital twins
by: Sun, Xiaowu, et al.
Published: (2025)

Deep generative models as an adversarial attack strategy for tabular machine learning
by: Dyrmishi, Salijona, et al.
Published: (2024)

Conditional deep generative models as surrogates for spatial field solution reconstruction with quantified uncertainty in Structural Health Monitoring applications
by: Silionis, Nicholas E., et al.
Published: (2023)

FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
by: Dong, Xiangyu, et al.
Published: (2025)

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2023)