Saved in:
| Main Authors: | Yang, Mengxi, Shi, Dai, Zheng, Xuebin, Yin, Jie, Gao, Junbin |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2201.04728 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Framelet-Based Blind Image Restoration with Minimax Concave Regularization
by: Zhang, Heng, et al.
Published: (2026)
by: Zhang, Heng, et al.
Published: (2026)
Quasi-Random Physics-informed Neural Networks
by: Yu, Tianchi, et al.
Published: (2025)
by: Yu, Tianchi, et al.
Published: (2025)
A Dimensionality Reduction Approach for Convolutional Neural Networks
by: Meneghetti, Laura, et al.
Published: (2021)
by: Meneghetti, Laura, et al.
Published: (2021)
Data-Adaptive Graph Framelets with Generalized Vanishing Moments for Graph Machine Learning
by: Zheng, Ruigang, et al.
Published: (2023)
by: Zheng, Ruigang, et al.
Published: (2023)
KAN-GCN: Combining Kolmogorov-Arnold Network with Graph Convolution Network for an Accurate Ice Sheet Emulator
by: Liu, Zesheng, et al.
Published: (2025)
by: Liu, Zesheng, et al.
Published: (2025)
Graph-Instructed Neural Networks for parametric problems with varying boundary conditions
by: Della Santa, Francesco, et al.
Published: (2026)
by: Della Santa, Francesco, et al.
Published: (2026)
Graph Neural Networks for Emulation of Finite-Element Ice Dynamics in Greenland and Antarctic Ice Sheets
by: Koo, Younghyun, et al.
Published: (2024)
by: Koo, Younghyun, et al.
Published: (2024)
Graph Neural Network as Computationally Efficient Emulator of Ice-sheet and Sea-level System Model (ISSM)
by: Koo, Younghyun, et al.
Published: (2024)
by: Koo, Younghyun, et al.
Published: (2024)
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
by: Wang, Hong, et al.
Published: (2024)
by: Wang, Hong, et al.
Published: (2024)
Moving Sampling Physics-informed Neural Networks induced by Moving Mesh PDE
by: Yang, Yu, et al.
Published: (2023)
by: Yang, Yu, et al.
Published: (2023)
Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study
by: Ke, Yekun, et al.
Published: (2024)
by: Ke, Yekun, et al.
Published: (2024)
PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training
by: Yang, Shenghao, et al.
Published: (2026)
by: Yang, Shenghao, et al.
Published: (2026)
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices Approach
by: Li, Guoming, et al.
Published: (2024)
by: Li, Guoming, et al.
Published: (2024)
Quantum Neural Network Restatement of Markov Jump Process
by: Zarezadeh, Z., et al.
Published: (2025)
by: Zarezadeh, Z., et al.
Published: (2025)
Robust Non-Linear Correlations via Polynomial Regression
by: Giuliani, Luca, et al.
Published: (2025)
by: Giuliani, Luca, et al.
Published: (2025)
V-ABFT: Variance-Based Adaptive Threshold for Fault-Tolerant Matrix Multiplication in Mixed-Precision Deep Learning
by: Gao, Yiheng, et al.
Published: (2026)
by: Gao, Yiheng, et al.
Published: (2026)
Learning from Integral Losses in Physics Informed Neural Networks
by: Saleh, Ehsan, et al.
Published: (2023)
by: Saleh, Ehsan, et al.
Published: (2023)
Robust low-rank training via approximate orthonormal constraints
by: Savostianova, Dayana, et al.
Published: (2023)
by: Savostianova, Dayana, et al.
Published: (2023)
Towards Faster Matrix Diagonalization with Graph Isomorphism Networks and the AlphaZero Framework
by: Zollicoffer, Geigh, et al.
Published: (2024)
by: Zollicoffer, Geigh, et al.
Published: (2024)
STNet: Spectral Transformation Network for Solving Operator Eigenvalue Problem
by: Wang, Hong, et al.
Published: (2025)
by: Wang, Hong, et al.
Published: (2025)
AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures
by: Gao, Yihang, et al.
Published: (2024)
by: Gao, Yihang, et al.
Published: (2024)
Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems using Transfer Learning
by: Mustajab, Abdul Hannan, et al.
Published: (2024)
by: Mustajab, Abdul Hannan, et al.
Published: (2024)
Multiscale Graph Neural Network for Turbulent Flow-Thermal Prediction Around a Complex-Shaped Pin-Fin
by: Raut, Riddhiman, et al.
Published: (2025)
by: Raut, Riddhiman, et al.
Published: (2025)
Autoregression-Free Neural Operators for Time-Dependent PDEs
by: Zhang, Jiaquan, et al.
Published: (2026)
by: Zhang, Jiaquan, et al.
Published: (2026)
CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
by: Hou, Xianglong, et al.
Published: (2025)
by: Hou, Xianglong, et al.
Published: (2025)
Online Pseudo-average Shifting Attention(PASA) for Robust Low-precision LLM Inference: Algorithms and Numerical Analysis
by: Cheng, Long, et al.
Published: (2025)
by: Cheng, Long, et al.
Published: (2025)
Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter
by: Wang, Hong, et al.
Published: (2025)
by: Wang, Hong, et al.
Published: (2025)
ProFlow: Zero-Shot Physics-Consistent Sampling via Proximal Flow Guidance
by: Yu, Zichao, et al.
Published: (2026)
by: Yu, Zichao, et al.
Published: (2026)
PDE Generalization of In-Context Operator Networks: A Study on 1D Scalar Nonlinear Conservation Laws
by: Yang, Liu, et al.
Published: (2024)
by: Yang, Liu, et al.
Published: (2024)
ELM-DeepONets: Backpropagation-Free Training of Deep Operator Networks via Extreme Learning Machines
by: Son, Hwijae
Published: (2025)
by: Son, Hwijae
Published: (2025)
Neural Control Variates with Automatic Integration
by: Li, Zilu, et al.
Published: (2024)
by: Li, Zilu, et al.
Published: (2024)
UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss
by: Wang, Zhichao, et al.
Published: (2025)
by: Wang, Zhichao, et al.
Published: (2025)
Parametrizing Convex Sets Using Sublinear Neural Networks
by: Martinet, Eloi
Published: (2026)
by: Martinet, Eloi
Published: (2026)
Neural Operators with Localized Integral and Differential Kernels
by: Liu-Schiaffini, Miguel, et al.
Published: (2024)
by: Liu-Schiaffini, Miguel, et al.
Published: (2024)
CATO: Charted Attention for Neural PDE Operators
by: Cheng, Chun-Wun, et al.
Published: (2026)
by: Cheng, Chun-Wun, et al.
Published: (2026)
Framelets and Wavelets with Mixed Dilation Factors
by: Lu, Ran
Published: (2025)
by: Lu, Ran
Published: (2025)
Graph Neural Network Surrogates for Contacting Deformable Bodies with Necessary and Sufficient Contact Detection
by: Dubey, Vijay K., et al.
Published: (2025)
by: Dubey, Vijay K., et al.
Published: (2025)
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems
by: Zhang, Ce, et al.
Published: (2023)
by: Zhang, Ce, et al.
Published: (2023)
Monte Carlo-Type Neural Operator for Differential Equations
by: Choutri, Salah Eddine, et al.
Published: (2025)
by: Choutri, Salah Eddine, et al.
Published: (2025)
Spectral Informed Neural Network: An Efficient and Low-Memory PINN
by: Yu, Tianchi, et al.
Published: (2024)
by: Yu, Tianchi, et al.
Published: (2024)
Similar Items
-
Framelet-Based Blind Image Restoration with Minimax Concave Regularization
by: Zhang, Heng, et al.
Published: (2026) -
Quasi-Random Physics-informed Neural Networks
by: Yu, Tianchi, et al.
Published: (2025) -
A Dimensionality Reduction Approach for Convolutional Neural Networks
by: Meneghetti, Laura, et al.
Published: (2021) -
Data-Adaptive Graph Framelets with Generalized Vanishing Moments for Graph Machine Learning
by: Zheng, Ruigang, et al.
Published: (2023) -
KAN-GCN: Combining Kolmogorov-Arnold Network with Graph Convolution Network for an Accurate Ice Sheet Emulator
by: Liu, Zesheng, et al.
Published: (2025)