Scalable physical source-to-field inference with hypernetworks
Fuente:
arXiv
Saved in:
| Main Authors: | James, Berian, Pollok, Stefan, Peis, Ignacio, Baker, Elizabeth Louise, Frellsen, Jes, Bjørk, Rasmus |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The magnetic scalar potential for a rectangular prism
by: James, Berian, et al.
Published: (2025)
by: James, Berian, 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)
by: Padmanabha, Govinda Anantha, et al.
Published: (2024)
Convergence of physics-informed neural networks modeling time-harmonic wave fields
by: Schoder, Stefan, et al.
Published: (2025)
by: Schoder, Stefan, et al.
Published: (2025)
When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks
by: Drinkall, Felix, et al.
Published: (2025)
by: Drinkall, Felix, et al.
Published: (2025)
Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks
by: Luo, Junliang, et al.
Published: (2025)
by: Luo, Junliang, et al.
Published: (2025)
CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm
by: Liu, Dingkun, et al.
Published: (2025)
by: Liu, Dingkun, 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)
by: Raut, Riddhiman, et al.
Published: (2024)
Physics-Informed Learning of Flow Distribution and Receiver Heat Losses in Parabolic Trough Solar Fields
by: Matthes, Stefan, et al.
Published: (2025)
by: Matthes, Stefan, et al.
Published: (2025)
Unsupervised full-field Bayesian inference of orthotropic hyperelasticity from a single biaxial test: a myocardial case study
by: Krijnen, Rogier P., et al.
Published: (2025)
by: Krijnen, Rogier P., et al.
Published: (2025)
Parameter Space Analysis through Guided Visual Interpolations
by: Kantz, Benedikt, et al.
Published: (2025)
by: Kantz, Benedikt, et al.
Published: (2025)
Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks
by: Eivazi, Hamidreza, et al.
Published: (2024)
by: Eivazi, Hamidreza, et al.
Published: (2024)
Aerodynamic force reconstruction using physics-informed Gaussian processes
by: Tondo, Gledson Rodrigo, et al.
Published: (2026)
by: Tondo, Gledson Rodrigo, et al.
Published: (2026)
Utilising physics-guided deep learning to overcome data scarcity
by: Bai, Jinshuai, et al.
Published: (2022)
by: Bai, Jinshuai, et al.
Published: (2022)
Learning solutions of parametric Navier-Stokes with physics-informed neural networks
by: Naderibeni, M., et al.
Published: (2024)
by: Naderibeni, M., et al.
Published: (2024)
Multifidelity linear regression for scientific machine learning from scarce data
by: Qian, Elizabeth, et al.
Published: (2024)
by: Qian, Elizabeth, et al.
Published: (2024)
Local learning for stable backpropagation-free neural network training towards physical learning
by: Guo, Yaqi, et al.
Published: (2026)
by: Guo, Yaqi, et al.
Published: (2026)
Financial Wind Tunnel: A Retrieval-Augmented Market Simulator
by: Cao, Bokai, et al.
Published: (2025)
by: Cao, Bokai, et al.
Published: (2025)
Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
by: Cheng, Qishuo, et al.
Published: (2024)
by: Cheng, Qishuo, et al.
Published: (2024)
Decoding RWA Tokenized U.S. Treasuries: Functional Dissection and Address Role Inference
by: Luo, Junliang, et al.
Published: (2025)
by: Luo, Junliang, et al.
Published: (2025)
UAMM: Price-oracle based Automated Market Maker
by: Im, Daniel Jiwoong, et al.
Published: (2023)
by: Im, Daniel Jiwoong, et al.
Published: (2023)
Diffusion-Augmented Reinforcement Learning for Robust Portfolio Optimization under Stress Scenarios
by: Choudhary, Himanshu, et al.
Published: (2025)
by: Choudhary, Himanshu, et al.
Published: (2025)
MLP, XGBoost, KAN, TDNN, and LSTM-GRU Hybrid RNN with Attention for SPX and NDX European Call Option Pricing
by: Ter-Avanesov, Boris, et al.
Published: (2024)
by: Ter-Avanesov, Boris, et al.
Published: (2024)
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations
by: Rezaei, Shahed, et al.
Published: (2024)
by: Rezaei, Shahed, et al.
Published: (2024)
Neural Persistence Dynamics
by: Zeng, Sebastian, et al.
Published: (2024)
by: Zeng, Sebastian, et al.
Published: (2024)
Large language models, physics-based modeling, experimental measurements: the trinity of data-scarce learning of polymer properties
by: Liu, Ning, et al.
Published: (2024)
by: Liu, Ning, et al.
Published: (2024)
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)
by: Chen, Jungang, et al.
Published: (2023)
Macroscopic transport patterns of UAV traffic in 3D anisotropic wind fields: A constraint-preserving hybrid PINN-FVM approach
by: Liang, Hanbing, et al.
Published: (2026)
by: Liang, Hanbing, et al.
Published: (2026)
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space
by: Koopas, Rasoul Najafi, et al.
Published: (2024)
by: Koopas, Rasoul Najafi, et al.
Published: (2024)
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)
by: Zhao, Yingxue, et al.
Published: (2026)
Reservoir History Matching of the Norne field with generative exotic priors and a coupled Mixture of Experts -- Physics Informed Neural Operator Forward Model
by: Etienam, Clement, et al.
Published: (2024)
by: Etienam, Clement, et al.
Published: (2024)
A Neural Operator based Hybrid Microscale Model for Multiscale Simulation of Rate-Dependent Materials
by: Jeyaraj, Dhananjeyan, et al.
Published: (2025)
by: Jeyaraj, Dhananjeyan, et al.
Published: (2025)
Integrating Domain Knowledge for Financial QA: A Multi-Retriever RAG Approach with LLMs
by: Zhang, Yukun, et al.
Published: (2025)
by: Zhang, Yukun, et al.
Published: (2025)
Energy-based physics-informed neural network for frictionless contact problems under large deformation
by: Bai, Jinshuai, et al.
Published: (2024)
by: Bai, Jinshuai, et al.
Published: (2024)
Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference
by: McQuarrie, Shane A., et al.
Published: (2025)
by: McQuarrie, Shane A., et al.
Published: (2025)
Design Editing for Offline Model-based Optimization
by: Yuan, Ye, et al.
Published: (2024)
by: Yuan, Ye, et al.
Published: (2024)
Machine Learning-Assisted Discovery of Flow Reactor Designs
by: Savage, Tom, et al.
Published: (2023)
by: Savage, Tom, et al.
Published: (2023)
Latent Generative Modeling of Random Fields from Limited Training Data
by: Warner, James E., et al.
Published: (2025)
by: Warner, James E., et al.
Published: (2025)
SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
by: Wu, Qilong, et al.
Published: (2024)
by: Wu, Qilong, et al.
Published: (2024)
SeQwen at the Financial Misinformation Detection Challenge Task: Sequential Learning for Claim Verification and Explanation Generation in Financial Domains
by: Purbey, Jebish, et al.
Published: (2024)
by: Purbey, Jebish, et al.
Published: (2024)
evoxels: A differentiable physics framework for voxel-based microstructure simulations
by: Daubner, Simon, et al.
Published: (2025)
by: Daubner, Simon, et al.
Published: (2025)
Similar Items
-
The magnetic scalar potential for a rectangular prism
by: James, Berian, 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) -
Convergence of physics-informed neural networks modeling time-harmonic wave fields
by: Schoder, Stefan, et al.
Published: (2025) -
When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks
by: Drinkall, Felix, et al.
Published: (2025) -
Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks
by: Luo, Junliang, et al.
Published: (2025)