Copertina

MTL-FNO: A Lightweight Multi-Task Fourier Neural Operator for Sparse Field Reconstruction

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ye, Siyu, Li, Shihang, Gong, Zhiqiang, Zhang, Benrong, Zhou, Weien, Huang, Yiyong, Yao, Wen
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Learning to Reconstruct Temperature Field from Sparse Observations with Implicit Physics Priors
di: Li, Shihang, et al.
Pubblicazione: (2025)

SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators
di: Elhadidy, Mahmoud, et al.
Pubblicazione: (2026)

LOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators
di: Kalimuthu, Marimuthu, et al.
Pubblicazione: (2025)

Hankel-FNO: Fast Underwater Acoustic Charting Via Physics-Encoded Fourier Neural Operator
di: Sun, Yifan, et al.
Pubblicazione: (2025)

DiffFNO: Diffusion Fourier Neural Operator
di: Liu, Xiaoyi, et al.
Pubblicazione: (2024)

HS-FNO: History-Space Fourier Neural Operator for Non-Markovian Partial Differential Equations
di: Shikhman, Lennon J.
Pubblicazione: (2026)

Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data
di: Liu, Xu, et al.
Pubblicazione: (2022)

MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver
di: Zheng, Yuepeng, et al.
Pubblicazione: (2025)

MscaleFNO: Multi-scale Fourier Neural Operator Learning for Oscillatory Function Spaces
di: You, Zhilin, et al.
Pubblicazione: (2024)

SynergyWarpNet: Attention-Guided Cooperative Warping for Neural Portrait Animation
di: Li, Shihang, et al.
Pubblicazione: (2025)

Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems
di: Huang, Xujia, et al.
Pubblicazione: (2024)

MgFNO: Multi-grid Architecture Fourier Neural Operator for Parametric Partial Differential Equations
di: Guo, Zi-Hao, et al.
Pubblicazione: (2024)

DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data
di: Ye, Hanrong, et al.
Pubblicazione: (2024)

V2Rho-FNO: Fourier Neural Operator for Electronic Density Prediction
di: Jin, Yingdi, et al.
Pubblicazione: (2026)

STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Map
di: Sherif, Ammar, et al.
Pubblicazione: (2023)

MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning
di: Yang, Yaming, et al.
Pubblicazione: (2024)

MTL-UE: Learning to Learn Nothing for Multi-Task Learning
di: Yu, Yi, et al.
Pubblicazione: (2025)

Component Fourier Neural Operator for Singularly Perturbed Differential Equations
di: Li, Ye, et al.
Pubblicazione: (2024)

SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark
di: Wen, Rui, et al.
Pubblicazione: (2025)

Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning
di: Wang, Zedong, et al.
Pubblicazione: (2025)

LDC-MTL: Balancing Multi-Task Learning through Scalable Loss Discrepancy Control
di: Xiao, Peiyao, et al.
Pubblicazione: (2025)

MTL-MAD: Multi-Task Learners are Effective Medical Anomaly Detectors
di: Bercean, Bogdan Alexandru, et al.
Pubblicazione: (2026)

Multi-Resolution Active Learning of Fourier Neural Operators
di: Li, Shibo, et al.
Pubblicazione: (2023)

Analysis of Fourier Neural Operators via Effective Field Theory
di: Kim, Taeyoung
Pubblicazione: (2025)

Time-varying Factor Augmented Vector Autoregression with Grouped Sparse Autoencoder
di: Luo, Yiyong, et al.
Pubblicazione: (2025)

FNO$^{\angle θ}$: Extended Fourier neural operator for learning state and optimal control of distributed parameter systems
di: Li, Zhexian, et al.
Pubblicazione: (2026)

RobuMTL: Enhancing Multi-Task Learning Robustness Against Weather Conditions
di: Shaffee, Tasneem, et al.
Pubblicazione: (2026)

Isotropic Fourier Neural Operators
di: Staddon, Michael F.
Pubblicazione: (2026)

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images
di: Jeon, Jinsung, et al.
Pubblicazione: (2024)

TurboFNO: High-Performance Fourier Neural Operator with Fused FFT-GEMM-iFFT on GPU
di: Wu, Shixun, et al.
Pubblicazione: (2025)

MTL-Split: Multi-Task Learning for Edge Devices using Split Computing
di: Capogrosso, Luigi, et al.
Pubblicazione: (2024)

Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective
di: Koshizuka, Takeshi, et al.
Pubblicazione: (2023)

Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
di: Luo, Xihaier, et al.
Pubblicazione: (2024)

Direct Routing Gradient (DRGrad): A Personalized Information Surgery for Multi-Task Learning (MTL) Recommendations
di: Liu, Yuguang, et al.
Pubblicazione: (2025)

Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
di: Zhu, Min, et al.
Pubblicazione: (2023)

Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach
di: Zhang, Qian, et al.
Pubblicazione: (2026)

Neural Operators for Multi-Task Control and Adaptation
di: Sewell, David, et al.
Pubblicazione: (2026)

Sparse-to-Field Reconstruction via Stochastic Neural Dynamic Mode Decomposition
di: Kim, Yujin, et al.
Pubblicazione: (2025)

An ALE-Consistent Graph Neural Operator-Transformer Framework for Fluid-Structure Interaction
di: Zhao, Shihang, et al.
Pubblicazione: (2026)

Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
di: Chu, Mengyu, et al.
Pubblicazione: (2022)