A real-time battle situation intelligent awareness system based on Meta-learning & RNN
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Yuchun, Lin, Zihan, Wang, Xize, Liu, Chunyang, Wu, Liaoyuan, Zhang, Fang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Solving Partial Differential Equations with Random Feature Models
by: Liao, Chunyang
Published: (2024)
by: Liao, Chunyang
Published: (2024)
Cauchy Random Features for Operator Learning in Sobolev Space
by: Liao, Chunyang, et al.
Published: (2025)
by: Liao, Chunyang, et al.
Published: (2025)
Deep set based operator learning with uncertainty quantification
by: Ma, Lei, et al.
Published: (2025)
by: Ma, Lei, et al.
Published: (2025)
Machine learning enhanced real-time aerodynamic forces prediction based on sparse pressure sensor inputs
by: Duan, Junming, et al.
Published: (2023)
by: Duan, Junming, et al.
Published: (2023)
Differentiable Inverse Modeling with Physics-Constrained Latent Diffusion for Heterogeneous Subsurface Parameter Fields
by: Lin, Zihan, et al.
Published: (2025)
by: Lin, Zihan, et al.
Published: (2025)
Long-term simulation of physical and mechanical behaviors using curriculum-transfer-learning based physics-informed neural networks
by: Guo, Yuan, et al.
Published: (2025)
by: Guo, Yuan, et al.
Published: (2025)
A multifidelity approach to continual learning for physical systems
by: Howard, Amanda, et al.
Published: (2023)
by: Howard, Amanda, et al.
Published: (2023)
Learning cardiac activation and repolarization times with operator learning
by: Centofanti, Edoardo, et al.
Published: (2025)
by: Centofanti, Edoardo, et al.
Published: (2025)
Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach
by: Fang, Zhiwei, et al.
Published: (2023)
by: Fang, Zhiwei, et al.
Published: (2023)
Orthogonal greedy algorithm for linear operator learning with shallow neural network
by: Lin, Ye, et al.
Published: (2025)
by: Lin, Ye, et al.
Published: (2025)
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models
by: Tomasetto, Matteo, et al.
Published: (2024)
by: Tomasetto, Matteo, et al.
Published: (2024)
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems
by: Wang, Xintong, et al.
Published: (2025)
by: Wang, Xintong, et al.
Published: (2025)
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
by: Arisaka, Sohei, et al.
Published: (2024)
by: Arisaka, Sohei, et al.
Published: (2024)
U-HNO: A U-shaped Hybrid Neural Operator with Sparse-Point Adaptive Routing for Non-stationary PDE Dynamics
by: Ma, Yingzhe, et al.
Published: (2026)
by: Ma, Yingzhe, et al.
Published: (2026)
Sparse RBF Networks for PDEs and nonlocal equations: function space theory, operator calculus, and training algorithms
by: Shao, Zihan, et al.
Published: (2026)
by: Shao, Zihan, et al.
Published: (2026)
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
by: Shao, Zihan, et al.
Published: (2025)
by: Shao, Zihan, et al.
Published: (2025)
Geometry-aware training of factorized layers in tensor Tucker format
by: Zangrando, Emanuele, et al.
Published: (2023)
by: Zangrando, Emanuele, et al.
Published: (2023)
Regression-aware decompositions
by: Tygert, Mark
Published: (2017)
by: Tygert, Mark
Published: (2017)
Probabilistic operator learning: generative modeling and uncertainty quantification for foundation models of differential equations
by: Zhang, Benjamin J., et al.
Published: (2025)
by: Zhang, Benjamin J., et al.
Published: (2025)
KD-PINN: Knowledge-Distilled PINNs for ultra-low-latency real-time neural PDE solvers
by: Bounja, Karim, et al.
Published: (2025)
by: Bounja, Karim, et al.
Published: (2025)
Physics-aware deep learning framework for the limited aperture inverse obstacle scattering problem
by: Yin, Yunwen, et al.
Published: (2024)
by: Yin, Yunwen, et al.
Published: (2024)
A deformation-based framework for learning solution mappings of PDEs defined on varying domains
by: Xiao, Shanshan, et al.
Published: (2024)
by: Xiao, Shanshan, et al.
Published: (2024)
Physics-based machine learning for fatigue lifetime prediction under non-uniform loading scenarios
by: Baktheer, Abedulgader, et al.
Published: (2025)
by: Baktheer, Abedulgader, et al.
Published: (2025)
Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov Arnold Networks
by: Wang, Yizheng, et al.
Published: (2024)
by: Wang, Yizheng, et al.
Published: (2024)
Training-free score-based diffusion for parameter-dependent stochastic dynamical systems
by: Yang, Minglei, et al.
Published: (2026)
by: Yang, Minglei, et al.
Published: (2026)
LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models
by: Budzinskiy, Stanislav, et al.
Published: (2026)
by: Budzinskiy, Stanislav, et al.
Published: (2026)
Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations
by: Zhang, Huan, et al.
Published: (2024)
by: Zhang, Huan, et al.
Published: (2024)
Structure-preserving neural networks for the regularized entropy-based closure of the Boltzmann moment system
by: Schotthöfer, Steffen, et al.
Published: (2024)
by: Schotthöfer, Steffen, et al.
Published: (2024)
Regional climate projections using a deep-learning-based model-ranking and downscaling framework: Application to European climate zones
by: Loganathan, Parthiban, et al.
Published: (2025)
by: Loganathan, Parthiban, et al.
Published: (2025)
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
by: Brivio, Simone, et al.
Published: (2024)
by: Brivio, Simone, et al.
Published: (2024)
A note on continuous-time online learning
by: Ying, Lexing
Published: (2024)
by: Ying, Lexing
Published: (2024)
Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models
by: Tomasetto, Matteo, et al.
Published: (2024)
by: Tomasetto, Matteo, et al.
Published: (2024)
Smoothness Adaptivity in Constant-Depth Neural Networks: Optimal Rates via Smooth Activations
by: Liu, Yuhao, et al.
Published: (2026)
by: Liu, Yuhao, et al.
Published: (2026)
Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations
by: Xu, Tengfei, et al.
Published: (2023)
by: Xu, Tengfei, et al.
Published: (2023)
Nonlinear model reduction for operator learning
by: Eivazi, Hamidreza, et al.
Published: (2024)
by: Eivazi, Hamidreza, et al.
Published: (2024)
Approximation and learning with compositional tensor trains
by: Eigel, Martin, et al.
Published: (2025)
by: Eigel, Martin, et al.
Published: (2025)
Symmetry group based domain decomposition to enhance physics-informed neural networks for solving partial differential equations
by: Liu, Ye, et al.
Published: (2024)
by: Liu, Ye, et al.
Published: (2024)
Deep learning based numerical approximation algorithms for stochastic partial differential equations
by: Beck, Christian, et al.
Published: (2020)
by: Beck, Christian, et al.
Published: (2020)
Structure-preserving learning for multi-symplectic PDEs
by: Yıldız, Süleyman, et al.
Published: (2024)
by: Yıldız, Süleyman, et al.
Published: (2024)
Meshless method stencil evaluation with machine learning
by: Rot, Miha, et al.
Published: (2022)
by: Rot, Miha, et al.
Published: (2022)
Similar Items
-
Solving Partial Differential Equations with Random Feature Models
by: Liao, Chunyang
Published: (2024) -
Cauchy Random Features for Operator Learning in Sobolev Space
by: Liao, Chunyang, et al.
Published: (2025) -
Deep set based operator learning with uncertainty quantification
by: Ma, Lei, et al.
Published: (2025) -
Machine learning enhanced real-time aerodynamic forces prediction based on sparse pressure sensor inputs
by: Duan, Junming, et al.
Published: (2023) -
Differentiable Inverse Modeling with Physics-Constrained Latent Diffusion for Heterogeneous Subsurface Parameter Fields
by: Lin, Zihan, et al.
Published: (2025)