A Kolmogorov-Arnold Networks-Based Model for Forecasting of Natural Gas Consumption DOI
Kürşad Arslan, Emrah Dönmez

Опубликована: Янв. 1, 2024

Язык: Английский

The Mathematics of Kolmogorov-Arnold-Networks versus Artificial Neural Networks DOI

Miquel Noguer I Alonso

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Three operator learning models for solving boundary integral equations in 2D connected domains DOI
Bin Meng, Yutong Lu, Ying Jiang

и другие.

Applied Mathematical Modelling, Год журнала: 2025, Номер unknown, С. 116034 - 116034

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

A theory of functional connections-based method for orbital pursuit-evasion games with analytic satisfaction of rendezvous constraints DOI
Chengming Zhang, Yanwei Zhu,

Leping Yang

и другие.

Aerospace Science and Technology, Год журнала: 2025, Номер unknown, С. 110142 - 110142

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

SK-PINN: Accelerated physics-informed deep learning by smoothing kernel gradients DOI
Cunliang Pan, Chengxuan Li, Yü Liu

и другие.

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2025, Номер 440, С. 117956 - 117956

Опубликована: Март 30, 2025

Язык: Английский

Процитировано

0

Predicting crack nucleation and propagation in brittle materials using Deep Operator Networks with diverse trunk architectures DOI

Elham Kiyani,

M. Manav,

Nikhil Kadivar

и другие.

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2025, Номер 441, С. 117984 - 117984

Опубликована: Апрель 19, 2025

Язык: Английский

Процитировано

0

GDKansformer: A Group-wise Dynamic Kolmogorov-Arnold Transformer with Multi-view Gated Attention for Pathological Image Diagnosis DOI
Xiaoyan Lu, Xun Gong, Y. Chen

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 127978 - 127978

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Extraction and reconstruction of variable-coefficient governing equations using Res-KAN integrating sparse regression DOI
Maozu Guo,

Xing Lü,

Yongtao Jin

и другие.

Physica D Nonlinear Phenomena, Год журнала: 2025, Номер unknown, С. 134689 - 134689

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Scaled-cPIKANs: Spatial Variable and Residual Scaling in Chebyshev-based Physics-informed Kolmogorov-Arnold Networks DOI Creative Commons
F. Mostajeran, Salah A. Faroughi

Journal of Computational Physics, Год журнала: 2025, Номер unknown, С. 114116 - 114116

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Kan-Enhanced Deep Reinforcement Learning for Chaos Control Achieving Rapid Stabilization Via Minor Perturbations DOI

Tongtao Liu,

Yongping Zhang

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Evaluating Kolmogorov–Arnold Networks for Scientific Discovery: A Simple Yet Effective Approach DOI Open Access
Qixuan Sun

Опубликована: Авг. 19, 2024

Kolmogorov–Arnold Network (KAN) is an emerging interpretable neural network compared to fully black-box MLPs. Recently, works focus on comprehensive and fair comparisons between KAN MLP in various tasks. However, these didn't the strongest advantage of KAN: generating symbolic outputs. The ability provide scientific insights or even discover new science under-examined. In this work, we propose several novel metrics measure how well a performs function fitting: R^2-Mean, weighted R^2-complexity loss, ranking metrics. We also metric determine mathematical complexity target evaluate with functions different complexity. Additionally, tried inputs ranges find effect normalization.

Язык: Английский

Процитировано

0