:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Serrano, Louis, Wang, Thomas X, Naour, Etienne Le, Vittaut, Jean-Noël, Gallinari, Patrick
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2406.02176
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
di: Koupaï, Armand Kassaï, et al.
Pubblicazione: (2024)

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
di: Naour, Etienne Le, et al.
Pubblicazione: (2023)

ENMA: Tokenwise Autoregression for Generative Neural PDE Operators
di: Koupaï, Armand Kassaï, et al.
Pubblicazione: (2025)

Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods
di: Boudec, Lise Le, et al.
Pubblicazione: (2024)

MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling
di: Naour, Etienne Le, et al.
Pubblicazione: (2025)

WindDragon: Enhancing wind power forecasting with Automated Deep Learning
di: Keisler, Julie, et al.
Pubblicazione: (2024)

Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
di: Serrano, Louis, et al.
Pubblicazione: (2024)

Are Time-Indexed Foundation Models the Future of Time Series Imputation?
di: Naour, Etienne Le, et al.
Pubblicazione: (2025)

Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations
di: Bhan, Milan, et al.
Pubblicazione: (2024)

AROMA: Autonomous Rank-one Matrix Adaptation
di: Sheng, Hao Nan, et al.
Pubblicazione: (2025)

On the Role of Reversible Instance Normalization
di: Berthelier, Gaspard, et al.
Pubblicazione: (2026)

Efficient Generative Transformer Operators For Million-Point PDEs
di: Koupaï, Armand Kassaï, et al.
Pubblicazione: (2025)

DREAMS: Preserving both Local and Global Structure in Dimensionality Reduction
di: Kury, Noël, et al.
Pubblicazione: (2025)

Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS
di: Berthelier, Gaspard, et al.
Pubblicazione: (2026)

Latent Neural Operator for Solving Forward and Inverse PDE Problems
di: Wang, Tian, et al.
Pubblicazione: (2024)

AROMA: Augmented Reasoning Over a Multimodal Architecture for Virtual Cell Genetic Perturbation Modeling
di: Wang, Zhenyu, et al.
Pubblicazione: (2026)

Field-Space Attention for Structure-Preserving Earth System Transformers
di: Witte, Maximilian, et al.
Pubblicazione: (2025)

Generative Latent Neural PDE Solver using Flow Matching
di: Li, Zijie, et al.
Pubblicazione: (2025)

Learning Physically Consistent Lagrangian Control Models Without Acceleration Measurements
di: Laiche, Ibrahim, et al.
Pubblicazione: (2025)

UP-dROM : Uncertainty-Aware and Parametrised dynamic Reduced-Order Model, application to unsteady flows
di: Zighed, Ismaël, et al.
Pubblicazione: (2025)

Latent Graph Learning in Generative Models of Neural Signals
di: Kodama, Nathan X., et al.
Pubblicazione: (2025)

Reciprocal Latent Fields for Precomputed Sound Propagation
di: Seuté, Hugo, et al.
Pubblicazione: (2026)

Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators
di: Lu, Xiaoxiao, et al.
Pubblicazione: (2026)

Text2PDE: Latent Diffusion Models for Accessible Physics Simulation
di: Zhou, Anthony, et al.
Pubblicazione: (2024)

Structure-Aware Epistemic Uncertainty Quantification for Neural Operator PDE Surrogates
di: Song, Haoze, et al.
Pubblicazione: (2026)

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields
di: Kofinas, Miltiadis, et al.
Pubblicazione: (2023)

Spatial Bayesian Neural Networks
di: Zammit-Mangion, Andrew, et al.
Pubblicazione: (2023)

Latent Neural-ODE for Model-Informed Precision Dosing: Overcoming Structural Assumptions in Pharmacokinetics
di: Maurel, Benjamin, et al.
Pubblicazione: (2026)

Variational quantization for state space models
di: David, Etienne, et al.
Pubblicazione: (2024)

Posterior-First Neural PDE Simulation: Inferring Hidden Problem State from a Single Field
di: Wang, Wenshuo, et al.
Pubblicazione: (2026)

A PDE-Informed Latent Diffusion Model for 2-m Temperature Downscaling
di: Rosu, Paul, et al.
Pubblicazione: (2025)

Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
di: Zhou, Hang, et al.
Pubblicazione: (2024)

Generative diffusion models from a PDE perspective
di: Cao, Fei, et al.
Pubblicazione: (2025)

Adversarial Learning for Neural PDE Solvers with Sparse Data
di: Gong, Yunpeng, et al.
Pubblicazione: (2024)

Physics-Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity
di: Garban, Manuel Ricardo Guevara, et al.
Pubblicazione: (2025)

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
di: Cheng, Ze, et al.
Pubblicazione: (2025)

Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
di: Li, Zijie, et al.
Pubblicazione: (2024)

Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
di: Knigge, David M., et al.
Pubblicazione: (2024)

Topological Spatial Graph Coarsening
di: Calissano, Anna, et al.
Pubblicazione: (2025)

Adaptive Mesh-Quantization for Neural PDE Solvers
di: Dool, Winfried van den, et al.
Pubblicazione: (2025)