Saved in:
| Main Authors: | Boudec, Lise Le, de Bezenac, Emmanuel, Serrano, Louis, Regueiro-Espino, Ramon Daniel, Yin, Yuan, Gallinari, Patrick |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.06820 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ENMA: Tokenwise Autoregression for Generative Neural PDE Operators
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
Efficient Generative Transformer Operators For Million-Point PDEs
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
by: Koupaï, Armand Kassaï, et al.
Published: (2024)
by: Koupaï, Armand Kassaï, et al.
Published: (2024)
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
by: Serrano, Louis, et al.
Published: (2024)
by: Serrano, Louis, et al.
Published: (2024)
Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
by: Serrano, Louis, et al.
Published: (2024)
by: Serrano, Louis, et al.
Published: (2024)
Nodal Hybrid Neural Solvers for Parametric PDE Systems
by: Liu, Yun, et al.
Published: (2025)
by: Liu, Yun, et al.
Published: (2025)
Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
by: Naour, Etienne Le, et al.
Published: (2023)
by: Naour, Etienne Le, et al.
Published: (2023)
Active Learning for Neural PDE Solvers
by: Musekamp, Daniel, et al.
Published: (2024)
by: Musekamp, Daniel, et al.
Published: (2024)
Rigidity and flexibility results for groups with a common cocompact envelope
by: Boudec, Adrien Le
Published: (2025)
by: Boudec, Adrien Le
Published: (2025)
Learning PDE Solvers with Physics and Data: A Unifying View of Physics-Informed Neural Networks and Neural Operators
by: Dai, Yilong, et al.
Published: (2026)
by: Dai, Yilong, et al.
Published: (2026)
Physics-Informed Neural PDE Solvers via Spatio-Temporal MeanFlow
by: Bai, Hanru, et al.
Published: (2026)
by: Bai, Hanru, et al.
Published: (2026)
Brain-Inspired Physics-Informed Neural Networks: Bare-Minimum Neural Architectures for PDE Solvers
by: Markidis, Stefano
Published: (2024)
by: Markidis, Stefano
Published: (2024)
Learning Neural PDE Solvers with Convergence Guarantees
by: Hsieh, Jun-Ting, et al.
Published: (2019)
by: Hsieh, Jun-Ting, et al.
Published: (2019)
Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers
by: Zhang, Enrui, et al.
Published: (2022)
by: Zhang, Enrui, et al.
Published: (2022)
On closure operations in the space of subgroups and applications
by: Francoeur, Dominik, et al.
Published: (2024)
by: Francoeur, Dominik, et al.
Published: (2024)
Lattices determined by their commensurator
by: Boudec, Adrien Le, et al.
Published: (2026)
by: Boudec, Adrien Le, et al.
Published: (2026)
Adversarial Learning for Neural PDE Solvers with Sparse Data
by: Gong, Yunpeng, et al.
Published: (2024)
by: Gong, Yunpeng, et al.
Published: (2024)
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers
by: Pförtner, Marvin, et al.
Published: (2022)
by: Pförtner, Marvin, et al.
Published: (2022)
Physics Informed Differentiable Solvers for Learning Parametric Solution Manifolds in Heterogeneous Physical Systems
by: Panahi, Milad, et al.
Published: (2026)
by: Panahi, Milad, et al.
Published: (2026)
An operator preconditioning perspective on training in physics-informed machine learning
by: De Ryck, Tim, et al.
Published: (2023)
by: De Ryck, Tim, et al.
Published: (2023)
DGNN: A Neural PDE Solver Induced by Discontinuous Galerkin Methods
by: Chen, Guanyu, et al.
Published: (2025)
by: Chen, Guanyu, et al.
Published: (2025)
Ambient Physics: Training Neural PDE Solvers with Partial Observations
by: Majid, Harris Abdul, et al.
Published: (2026)
by: Majid, Harris Abdul, et al.
Published: (2026)
PT-PINNs: A Parametric Engineering Turbulence Solver based on Physics-Informed Neural Networks
by: Jiang, Liang, et al.
Published: (2025)
by: Jiang, Liang, et al.
Published: (2025)
Flowers: A Warp Drive for Neural PDE Solvers
by: Muser, Till, et al.
Published: (2026)
by: Muser, Till, et al.
Published: (2026)
Network-Calculus Service Curves of the Interleaved Regulator
by: Thomas, Ludovic, et al.
Published: (2023)
by: Thomas, Ludovic, et al.
Published: (2023)
Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
by: Zhou, Hang, et al.
Published: (2024)
by: Zhou, Hang, et al.
Published: (2024)
Adaptive Mesh-Quantization for Neural PDE Solvers
by: Dool, Winfried van den, et al.
Published: (2025)
by: Dool, Winfried van den, et al.
Published: (2025)
Physics-Informed Neural Networks and Neural Operators for Parametric PDEs
by: Zhang, Zhuo, et al.
Published: (2025)
by: Zhang, Zhuo, et al.
Published: (2025)
A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning
by: Toscano, Juan Diego, et al.
Published: (2025)
by: Toscano, Juan Diego, et al.
Published: (2025)
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
by: Lingsch, Levi, et al.
Published: (2023)
by: Lingsch, Levi, et al.
Published: (2023)
Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training
by: Zhao, Yequan, et al.
Published: (2025)
by: Zhao, Yequan, et al.
Published: (2025)
Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver
by: Sittoni, Pietro, et al.
Published: (2026)
by: Sittoni, Pietro, et al.
Published: (2026)
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
by: Horie, Masanobu, et al.
Published: (2024)
by: Horie, Masanobu, et al.
Published: (2024)
Inverse Evolution Data Augmentation for Neural PDE Solvers
by: Liu, Chaoyu, et al.
Published: (2025)
by: Liu, Chaoyu, et al.
Published: (2025)
Dynamical Measure Transport and Neural PDE Solvers for Sampling
by: Sun, Jingtong, et al.
Published: (2024)
by: Sun, Jingtong, et al.
Published: (2024)
Hamiltonian Neural PDE Solvers through Functional Approximation
by: Zhou, Anthony, et al.
Published: (2025)
by: Zhou, Anthony, et al.
Published: (2025)
Pre-Generating Multi-Difficulty PDE Data for Few-Shot Neural PDE Solvers
by: Choudhary, Naman, et al.
Published: (2025)
by: Choudhary, Naman, et al.
Published: (2025)
Learning Physically Consistent Lagrangian Control Models Without Acceleration Measurements
by: Laiche, Ibrahim, et al.
Published: (2025)
by: Laiche, Ibrahim, et al.
Published: (2025)
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
by: Zhang, Rui, et al.
Published: (2023)
by: Zhang, Rui, et al.
Published: (2023)
Neural PDE Solvers with Physics Constraints: A Comparative Study of PINNs, DRM, and WANs
by: Chen, Jiakang
Published: (2025)
by: Chen, Jiakang
Published: (2025)
Similar Items
-
ENMA: Tokenwise Autoregression for Generative Neural PDE Operators
by: Koupaï, Armand Kassaï, et al.
Published: (2025) -
Efficient Generative Transformer Operators For Million-Point PDEs
by: Koupaï, Armand Kassaï, et al.
Published: (2025) -
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
by: Koupaï, Armand Kassaï, et al.
Published: (2024) -
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
by: Serrano, Louis, et al.
Published: (2024) -
Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
by: Serrano, Louis, et al.
Published: (2024)