PowerMLP: An Efficient Version of KAN
Fuente:
arXiv
Saved in:
| Main Authors: | Qiu, Ruichen, Miao, Yibo, Wang, Shiwen, Yu, Lijia, Zhu, Yifan, Gao, Xiao-Shan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
KAN versus MLP on Irregular or Noisy Functions
by: Zeng, Chen, et al.
Published: (2024)
by: Zeng, Chen, et al.
Published: (2024)
SpectraKAN: Conditioning Spectral Operators
by: Cheng, Chun-Wun, et al.
Published: (2026)
by: Cheng, Chun-Wun, et al.
Published: (2026)
Free-RBF-KAN: Kolmogorov-Arnold Networks with Adaptive Radial Basis Functions for Efficient Function Learning
by: Chiu, Shao-Ting, et al.
Published: (2026)
by: Chiu, Shao-Ting, et al.
Published: (2026)
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions
by: Aghaei, Alireza Afzal
Published: (2024)
by: Aghaei, Alireza Afzal
Published: (2024)
FI-KAN: Fractal Interpolation Kolmogorov-Arnold Networks
by: N'guessan, Gnankan Landry Regis
Published: (2026)
by: N'guessan, Gnankan Landry Regis
Published: (2026)
ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations
by: Tang, Shanshan, et al.
Published: (2019)
by: Tang, Shanshan, et al.
Published: (2019)
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
by: Yu, Yifan, et al.
Published: (2025)
by: Yu, Yifan, et al.
Published: (2025)
rKAN: Rational Kolmogorov-Arnold Networks
by: Aghaei, Alireza Afzal
Published: (2024)
by: Aghaei, Alireza Afzal
Published: (2024)
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)
Understanding the Difficulty of Solving Cauchy Problems with PINNs
by: Wang, Tao, et al.
Published: (2024)
by: Wang, Tao, et al.
Published: (2024)
Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse Problems
by: Che, Baojun, et al.
Published: (2025)
by: Che, Baojun, et al.
Published: (2025)
Multivariate Density Estimation via Variance-Reduced Sketching
by: Peng, Yifan, et al.
Published: (2024)
by: Peng, Yifan, et al.
Published: (2024)
Sparse discovery of differential equations based on multi-fidelity Gaussian process
by: Meng, Yuhuang, et al.
Published: (2024)
by: Meng, Yuhuang, et al.
Published: (2024)
Resolution invariant deep operator network for PDEs with complex geometries
by: Huang, Jianguo, et al.
Published: (2024)
by: Huang, Jianguo, et al.
Published: (2024)
Lipschitz-Guided Design of Interpolation Schedules in Generative Models
by: Chen, Yifan, et al.
Published: (2025)
by: Chen, Yifan, et al.
Published: (2025)
Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport
by: Dang, Haoning, et al.
Published: (2026)
by: Dang, Haoning, et al.
Published: (2026)
Sharp Analysis of Power Iteration for Tensor PCA
by: Wu, Yuchen, et al.
Published: (2024)
by: Wu, Yuchen, et al.
Published: (2024)
Power Transform Revisited: Numerically Stable, and Federated
by: Xu, Xuefeng, et al.
Published: (2025)
by: Xu, Xuefeng, et al.
Published: (2025)
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts
by: Kratsios, Anastasis, et al.
Published: (2024)
by: Kratsios, Anastasis, et al.
Published: (2024)
Expressive Power of Deep Networks on Manifolds: Simultaneous Approximation
by: Zhou, Hanfei, et al.
Published: (2025)
by: Zhou, Hanfei, et al.
Published: (2025)
Neural parametric representations for thin-shell shape optimisation
by: Xiao, Xiao, et al.
Published: (2026)
by: Xiao, Xiao, et al.
Published: (2026)
Approximation Power of Deep Neural Networks: an explanatory mathematical survey
by: Davis, Owen, et al.
Published: (2022)
by: Davis, Owen, et al.
Published: (2022)
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)
Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training
by: Li, Qinglun, et al.
Published: (2025)
by: Li, Qinglun, et al.
Published: (2025)
Variationally correct operator learning: Reduced basis neural operator with a posteriori error estimation
by: Qiu, Yuan, et al.
Published: (2025)
by: Qiu, Yuan, et al.
Published: (2025)
FBSJNN: A Theoretically Interpretable and Efficiently Deep Learning method for Solving Partial Integro-Differential Equations
by: Ye, Zaijun, et al.
Published: (2024)
by: Ye, Zaijun, et al.
Published: (2024)
Lower Bounds for the Convergence of Tensor Power Iteration on Random Overcomplete Models
by: Wu, Yuchen, et al.
Published: (2022)
by: Wu, Yuchen, et al.
Published: (2022)
First-order PDES for Graph Neural Networks: Advection And Burgers Equation Models
by: Qu, Yifan, et al.
Published: (2024)
by: Qu, Yifan, et al.
Published: (2024)
Physics-embedded Fourier Neural Network for Partial Differential Equations
by: Xu, Qingsong, et al.
Published: (2024)
by: Xu, Qingsong, et al.
Published: (2024)
Radial Müntz-Szász Networks: Neural Architectures with Learnable Power Bases for Multidimensional Singularities
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)
by: N'guessan, Gnankan Landry Regis, et al.
Published: (2026)
Scale-Adaptive Generative Flows for Multiscale Scientific Data
by: Chen, Yifan, et al.
Published: (2025)
by: Chen, Yifan, et al.
Published: (2025)
Windowed Fourier Propagator: A Frequency-Local Neural Operator for Wave Equations in Inhomogeneous Media
by: Cai, Yiyang, et al.
Published: (2026)
by: Cai, Yiyang, et al.
Published: (2026)
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
by: Chen, Yifan, et al.
Published: (2023)
by: Chen, Yifan, et al.
Published: (2023)
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows
by: Chen, Yifan, et al.
Published: (2024)
by: Chen, Yifan, et al.
Published: (2024)
A Computationally Efficient Multidimensional Vision Transformer
by: Ichi, Alaa El, et al.
Published: (2026)
by: Ichi, Alaa El, et al.
Published: (2026)
Generalizability of Graph Neural Network Force Fields for Predicting Solid-State Properties
by: Mohanty, Shaswat, et al.
Published: (2024)
by: Mohanty, Shaswat, et al.
Published: (2024)
Sample Efficient Learning of Factored Embeddings of Tensor Fields
by: Heo, Taemin, et al.
Published: (2022)
by: Heo, Taemin, et al.
Published: (2022)
MgNO: Efficient Parameterization of Linear Operators via Multigrid
by: He, Juncai, et al.
Published: (2023)
by: He, Juncai, et al.
Published: (2023)
Efficient Tensor Completion Algorithms for Highly Oscillatory Operators
by: Singh, Navjot, et al.
Published: (2025)
by: Singh, Navjot, et al.
Published: (2025)
Efficient Differentiable Approximation of Generalized Low-rank Regularization
by: Li, Naiqi, et al.
Published: (2025)
by: Li, Naiqi, et al.
Published: (2025)
Similar Items
-
KAN versus MLP on Irregular or Noisy Functions
by: Zeng, Chen, et al.
Published: (2024) -
SpectraKAN: Conditioning Spectral Operators
by: Cheng, Chun-Wun, et al.
Published: (2026) -
Free-RBF-KAN: Kolmogorov-Arnold Networks with Adaptive Radial Basis Functions for Efficient Function Learning
by: Chiu, Shao-Ting, et al.
Published: (2026) -
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions
by: Aghaei, Alireza Afzal
Published: (2024) -
FI-KAN: Fractal Interpolation Kolmogorov-Arnold Networks
by: N'guessan, Gnankan Landry Regis
Published: (2026)