Saved in:
| Main Authors: | Serrano, Louis, Wang, Thomas X, Naour, Etienne Le, Vittaut, Jean-Noël, Gallinari, Patrick |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.02176 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
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)
ENMA: Tokenwise Autoregression for Generative Neural PDE Operators
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods
by: Boudec, Lise Le, et al.
Published: (2024)
by: Boudec, Lise Le, et al.
Published: (2024)
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling
by: Naour, Etienne Le, et al.
Published: (2025)
by: Naour, Etienne Le, et al.
Published: (2025)
WindDragon: Enhancing wind power forecasting with Automated Deep Learning
by: Keisler, Julie, et al.
Published: (2024)
by: Keisler, Julie, 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)
Are Time-Indexed Foundation Models the Future of Time Series Imputation?
by: Naour, Etienne Le, et al.
Published: (2025)
by: Naour, Etienne Le, et al.
Published: (2025)
Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations
by: Bhan, Milan, et al.
Published: (2024)
by: Bhan, Milan, et al.
Published: (2024)
AROMA: Autonomous Rank-one Matrix Adaptation
by: Sheng, Hao Nan, et al.
Published: (2025)
by: Sheng, Hao Nan, et al.
Published: (2025)
On the Role of Reversible Instance Normalization
by: Berthelier, Gaspard, et al.
Published: (2026)
by: Berthelier, Gaspard, et al.
Published: (2026)
Efficient Generative Transformer Operators For Million-Point PDEs
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
by: Koupaï, Armand Kassaï, et al.
Published: (2025)
DREAMS: Preserving both Local and Global Structure in Dimensionality Reduction
by: Kury, Noël, et al.
Published: (2025)
by: Kury, Noël, et al.
Published: (2025)
Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS
by: Berthelier, Gaspard, et al.
Published: (2026)
by: Berthelier, Gaspard, et al.
Published: (2026)
Latent Neural Operator for Solving Forward and Inverse PDE Problems
by: Wang, Tian, et al.
Published: (2024)
by: Wang, Tian, et al.
Published: (2024)
AROMA: Augmented Reasoning Over a Multimodal Architecture for Virtual Cell Genetic Perturbation Modeling
by: Wang, Zhenyu, et al.
Published: (2026)
by: Wang, Zhenyu, et al.
Published: (2026)
Field-Space Attention for Structure-Preserving Earth System Transformers
by: Witte, Maximilian, et al.
Published: (2025)
by: Witte, Maximilian, et al.
Published: (2025)
Generative Latent Neural PDE Solver using Flow Matching
by: Li, Zijie, et al.
Published: (2025)
by: Li, Zijie, 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)
UP-dROM : Uncertainty-Aware and Parametrised dynamic Reduced-Order Model, application to unsteady flows
by: Zighed, Ismaël, et al.
Published: (2025)
by: Zighed, Ismaël, et al.
Published: (2025)
Latent Graph Learning in Generative Models of Neural Signals
by: Kodama, Nathan X., et al.
Published: (2025)
by: Kodama, Nathan X., et al.
Published: (2025)
Reciprocal Latent Fields for Precomputed Sound Propagation
by: Seuté, Hugo, et al.
Published: (2026)
by: Seuté, Hugo, et al.
Published: (2026)
Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators
by: Lu, Xiaoxiao, et al.
Published: (2026)
by: Lu, Xiaoxiao, et al.
Published: (2026)
Text2PDE: Latent Diffusion Models for Accessible Physics Simulation
by: Zhou, Anthony, et al.
Published: (2024)
by: Zhou, Anthony, et al.
Published: (2024)
Structure-Aware Epistemic Uncertainty Quantification for Neural Operator PDE Surrogates
by: Song, Haoze, et al.
Published: (2026)
by: Song, Haoze, et al.
Published: (2026)
Latent Field Discovery In Interacting Dynamical Systems With Neural Fields
by: Kofinas, Miltiadis, et al.
Published: (2023)
by: Kofinas, Miltiadis, et al.
Published: (2023)
Spatial Bayesian Neural Networks
by: Zammit-Mangion, Andrew, et al.
Published: (2023)
by: Zammit-Mangion, Andrew, et al.
Published: (2023)
Latent Neural-ODE for Model-Informed Precision Dosing: Overcoming Structural Assumptions in Pharmacokinetics
by: Maurel, Benjamin, et al.
Published: (2026)
by: Maurel, Benjamin, et al.
Published: (2026)
Variational quantization for state space models
by: David, Etienne, et al.
Published: (2024)
by: David, Etienne, et al.
Published: (2024)
Posterior-First Neural PDE Simulation: Inferring Hidden Problem State from a Single Field
by: Wang, Wenshuo, et al.
Published: (2026)
by: Wang, Wenshuo, et al.
Published: (2026)
A PDE-Informed Latent Diffusion Model for 2-m Temperature Downscaling
by: Rosu, Paul, et al.
Published: (2025)
by: Rosu, Paul, et al.
Published: (2025)
Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
by: Zhou, Hang, et al.
Published: (2024)
by: Zhou, Hang, et al.
Published: (2024)
Generative diffusion models from a PDE perspective
by: Cao, Fei, et al.
Published: (2025)
by: Cao, Fei, et al.
Published: (2025)
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 Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity
by: Garban, Manuel Ricardo Guevara, et al.
Published: (2025)
by: Garban, Manuel Ricardo Guevara, et al.
Published: (2025)
Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
by: Cheng, Ze, et al.
Published: (2025)
by: Cheng, Ze, et al.
Published: (2025)
Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
by: Li, Zijie, et al.
Published: (2024)
by: Li, Zijie, et al.
Published: (2024)
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
by: Knigge, David M., et al.
Published: (2024)
by: Knigge, David M., et al.
Published: (2024)
Topological Spatial Graph Coarsening
by: Calissano, Anna, et al.
Published: (2025)
by: Calissano, Anna, et al.
Published: (2025)
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)
Similar Items
-
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
by: Koupaï, Armand Kassaï, et al.
Published: (2024) -
Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
by: Naour, Etienne Le, et al.
Published: (2023) -
ENMA: Tokenwise Autoregression for Generative Neural PDE Operators
by: Koupaï, Armand Kassaï, et al.
Published: (2025) -
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods
by: Boudec, Lise Le, et al.
Published: (2024) -
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling
by: Naour, Etienne Le, et al.
Published: (2025)