Cover Image

Graph convolutional network as a fast statistical emulator for numerical ice sheet modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rahnemoonfar, Maryam, Koo, Younghyun
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computational Engineering, Finance, and Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Neural Network as Computationally Efficient Emulator of Ice-sheet and Sea-level System Model (ISSM)
by: Koo, Younghyun, et al.
Published: (2024)

Deep encoder-decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling
by: Ebbs-Picken, Takiah, et al.
Published: (2023)

Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
by: Chen, Jungang, et al.
Published: (2023)

Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming
by: Zhao, Yingxue, et al.
Published: (2026)

Ultra-short-term multi-step wind speed prediction for wind farms based on adaptive noise reduction technology and temporal convolutional network
by: Huang, Haojian
Published: (2023)

Hierarchical Information-sharing Convolutional Neural Network for the Prediction of Arctic Sea Ice Concentration and Velocity
by: Koo, Younghyun, et al.
Published: (2023)

Graph Neural Networks for Emulation of Finite-Element Ice Dynamics in Greenland and Antarctic Ice Sheets
by: Koo, Younghyun, et al.
Published: (2024)

Liquid Fourier Latent Dynamics Networks for fast GPU-based numerical simulations in computational cardiology
by: Salvador, Matteo, et al.
Published: (2024)

Prediction of Sea Ice Velocity and Concentration in the Arctic Ocean using Physics-informed Neural Network
by: Koo, Younghyun, et al.
Published: (2025)

Graph neural network-based surrogate modelling for real-time hydraulic prediction of urban drainage networks
by: Zhang, Zhiyu, et al.
Published: (2024)

Orientation-aware interaction-based deep material network in polycrystalline materials modeling
by: Wei, Ting-Ju, et al.
Published: (2025)

Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models
by: Padmanabha, Govinda Anantha, et al.
Published: (2024)

A Dual-Path neural network model to construct the flame nonlinear thermoacoustic response in the time domain
by: Wu, Jiawei, et al.
Published: (2024)

Interpretable long-term traffic modelling on national road networks using theory-informed deep learning
by: Li, Yue, et al.
Published: (2026)

SolarSeer: Ultrafast and accurate 24-hour solar irradiance forecasts outperforming numerical weather prediction across the USA
by: Bai, Mingliang, et al.
Published: (2025)

Physics-informed neural networks for parameter learning of wildfire spreading
by: Vogiatzoglou, Konstantinos, et al.
Published: (2024)

Predicting the fatigue life of asphalt concrete using neural networks
by: Houlík, Jakub, et al.
Published: (2024)

Discovering uncertainty: Gaussian constitutive neural networks with correlated weights
by: McCulloch, Jeremy A., et al.
Published: (2025)

Learning solutions of parametric Navier-Stokes with physics-informed neural networks
by: Naderibeni, M., et al.
Published: (2024)

Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval
by: Kandimalla, Eshwar Sai, et al.
Published: (2026)

Graph Multi-Similarity Learning for Molecular Property Prediction
by: Xu, Hao, et al.
Published: (2024)

Graph Laplacian-based Bayesian Multi-fidelity Modeling
by: Pinti, Orazio, et al.
Published: (2024)

Denoising diffusion networks for normative modeling in neuroimaging
by: Whitbread, Luke, et al.
Published: (2026)

Local learning for stable backpropagation-free neural network training towards physical learning
by: Guo, Yaqi, et al.
Published: (2026)

Interpreting core forms of urban morphology linked to urban functions with explainable graph neural network
by: Chen, Dongsheng, et al.
Published: (2025)

UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression
by: Gao, Mars Liyao, et al.
Published: (2026)

Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics
by: Garnier, Paul, et al.
Published: (2024)

CHAT: Beyond Contrastive Graph Transformer for Link Prediction in Heterogeneous Networks
by: Zhang, Shengming, et al.
Published: (2025)

Spatio-Temporal Attention Graph Neural Network: Explaining Causalities With Attention
by: Koistinen, Kosti, et al.
Published: (2026)

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting
by: Immordino, Gabriele, et al.
Published: (2024)

MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations
by: Deshpande, Saurabh, et al.
Published: (2022)

Heterogeneous Graph Representation of Stiffened Panels with Non-Uniform Boundary Conditions and Loads
by: Cai, Yuecheng, et al.
Published: (2025)

DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection
by: Kulkarni, Omkar, et al.
Published: (2025)

Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks
by: Wasi, Azmine Toushik, et al.
Published: (2024)

GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures
by: Hoffmann, Marco, et al.
Published: (2025)

Predicting Transonic Flowfields in Non-Homogeneous Unstructured Grids Using Autoencoder Graph Convolutional Networks
by: Immordino, Gabriele, et al.
Published: (2024)

LatticeGraphNet: A two-scale graph neural operator for simulating lattice structures
by: Jain, Ayush, et al.
Published: (2024)

EP-GAT: Energy-based Parallel Graph Attention Neural Network for Stock Trend Classification
by: Jiang, Zhuodong, et al.
Published: (2025)

B-XAIC Dataset: Benchmarking Explainable AI for Graph Neural Networks Using Chemical Data
by: Proszewska, Magdalena, et al.
Published: (2025)

Temperature Distribution Prediction in Laser Powder Bed Fusion using Transferable and Scalable Graph Neural Networks
by: Raut, Riddhiman, et al.
Published: (2024)