Kolmogorov-Arnold Networks

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Evaluating the Effectiveness of SechKAN on 1D Data
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Multivariate quantile regression via Kolmogorov-Arnold Networks
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Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
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Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems
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Kolmogorov--Arnold stability for discontinuous functions
Sep 7, 2026Sviatoslav V. DzhenzherKolmogorov-Arnold Networks Adversaries
InKAN: B-Spline KANs via Truncated Power Form
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RecKAN: Kolmogorov-Arnold Networks with a Learnable Recursive Polynomial Basis
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Kolmogorov--Arnold against bounded translations
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Predicting Functions, Not Features: KANs with Function-Space Joint-Embedding Predictive Learning for Medical Image Segmentation
Aug 12, 2026Yungeng Liu, Xuanzi Fang, Yuge Zhang +3Medical Image Segmentation Joint-Embedding Predictive Architectures
KANResDiff: Learning Local Residual Diffusion via Kolmogorov-Arnold Network for Ambiguous Medical Image Segmentation
Aug 12, 2026Fanding Li, Chenglin Wang, Xiangyu Li +9Medical Image Segmentation Diffusion Refinement
Quantum-Classical Physics-Informed Kolmogorov-Arnold Networks for Solving Fuzzy Differential Equations
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TravKAN: Fast and Interpretable Nonlinear Traversability Analysis with Kolmogorov-Arnold Networks
Aug 3, 2026Daniel Fusaro, Simone Mosco, Wanmeng Li +1Traversability Kolmogorov-Arnold Networks
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An Embedded RISC-V Evaluation of Kolmogorov--Arnold Networks in Hard-Constrained Recurrent Physics-Informed Models
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Jul 21, 2026Arthur Bizzi, Olga FinkStochastic Differential Equations Stochastic Dynamics
Kolmogorov--Arnold Networks for Small Language Models
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Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification
Jul 15, 2026Matthew Steven P. Toledo, Justine Raphael H. Jacinto, Vivekjeet Singh Chambal +3Kolmogorov-Arnold Networks Multilayer Perceptrons
STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting
Jul 14, 2026Sicong Lai, Yuehong Hu, Siru Zhong +3Spatio-Temporal Forecasting Kolmogorov-Arnold Networks
Neural Discovery of Memory and Nonlocal Kernels in Integro-Differential Equations with Constrained Kolmogorov--Arnold Networks
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Quantum Kolmogorov--Arnold representation theorem for continuous unitary-valued maps
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Enhanced Feature Extraction for IoT Network Intrusion Detection Using GNNs and KAN
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Geometry-Aware R-Structured Kolmogorov-Arnold Networks
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Jun 26, 2026Paula Carolina Lozano Duarte, Georgios Zervakis, Mehdi Tahoori +1Analog Kolmogorov-Arnold Networks
Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting
Jun 26, 2026Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +3Accurate Traffic Forecasting Llm-Based Forecasting Methods
Kolmogorov Arnold networks (KAN) for aerodynamic prediction: a comparison with MLPs and GNNs
Jun 25, 2026Miguel Jaraiz, Fermin Gutierrez, Pablo Yeste +4Kolmogorov-Arnold Networks Aerodynamics
Delta-Position Estimation-Based IMU Odometry: A Comparison of MLP and Kolmogorov-Arnold Networks
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Interpretable Concept-Guided Polynomial Tabular Kolmogorov-Arnold Network for EEG-Based Mild Cognitive Impairment Detection
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Jun 23, 2026Stefano Mereu, Oleksandr Kuznetsov, Gabriele Marchello +4Kolmogorov-Arnold Networks
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Jun 23, 2026Cheng Huang, Muyao Guan, Jairus Yougui Railey +6Air Pollution Spatio-Temporal Forecasting
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Interpretable Kolmogorov-Arnold Network with Feature-Isolated Temporal Attention Mechanism for Electricity Load Forecasting
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Low-power analogue neural networks with trainable nonlinear connections for continuous control
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Enhancing BiGRU with a KAN Block for Legal Document Classification and Summarization
May 27, 2026Ahmed Faizul Haque Dhrubo, Souvik Pramanik, Most. Aysha Siddika Sumona +4Summarization Kolmogorov-Arnold Networks
SCKAN: Structural Consensus-based KAN Prototype Learning for Semi-Supervised Pancreas Segmentation
May 26, 2026Yuqi Liu, Yufei Chen, Wei Fu +2Lesion Segmentation Learnable Prototypes
MSCGC-KAN: Multi-scale Causal Graph Convolution and Kolmogorov-Arnold Feature Mapping for EEG Emotion Recognition
May 26, 2026Haoliang Gong, Qingshan She, Jiale Xu +2Electroencephalography Foundation Models Emotion Recognition
KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis
May 21, 2026Stelios Boulitsakis Logothetis, Angela Wood, Pietro LiòSurvival Analysis Survival Predictions
Hybrid Kolmogorov-Arnold Network and XGBoost Framework for Week-Ahead Price Forecasting in Australia's National Electricity Market
May 21, 2026Houxuan Zhou, Sriram Prasad, Chenghao Huang +2Electricity Price Forecasting Electricity Markets
Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics
May 21, 2026Bhaskar Ranjan Karn, Dinesh KumarNeural Ordinary Differential Equations Kolmogorov-Arnold Networks
Approximation Theory for Neural Networks: Old and New
May 20, 2026Soumendu Sundar Mukherjee, Himasish TalukdarNeural-Network Approximation Approximation
Adaptive RBF-KAN: A Comparative Evaluation of Dynamic Shape Parameters in Kolmogorov-Arnold Networks
May 20, 2026Roberto Cavoretto, Alessandra De Rossi, Adeeba Haider +1Kolmogorov-Arnold Networks Radial Basis Function
KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition
May 18, 2026Mengxi Liu, Sizhen Bian, Vitor Fortes +5Human Activity Recognition Kolmogorov-Arnold Networks
Implicit spatial-frequency fusion of hyperspectral and lidar data via kolmogorov-arnold networks
May 14, 2026Zekun Long, Judy X. Yang, Jing Wang +3Frequency-Spatial Fusion Module Lidar

Sep 22, 2026 · cs.LGJ/K move · Enter open · S save

Evaluating the Effectiveness of SechKAN on 1D Data

Hoang-Thang Ta

The connection between the Kolmogorov-Arnold representation theorem (KART) and neural network design has led to the development of Kolmogorov-Arnold Networks (KANs), with applications ranging from STEM problems to AI tasks. In this paper, we investigate the effectiveness of a KAN variant, SechKAN, which relies on hyperbolic secant (sech) functions as basis functions, with a 1D projection to reduce the number of parameters to a level comparable to MLPs. We evaluate SechKAN on three 1D classification datasets: UCI Human Activity Recognition (UCI HAR), ElectricDevices, and Crop, and compare it with several effective networks, including EfficientKAN, MLP, CNN1D, ResNet1D, and DSCNN1D, using approximately comparable parameter budgets. The results indicate that SechKAN achieves competitive performance across the three datasets, with particularly strong performance on Crop. Ablation studies further show that grid size and normalization affect performance, suggesting that SechKAN's effectiveness depends on the dataset and architectural choices. Our source code and experimental implementation are publicly available at: https://github.com/hoangthangta/SechKAN_1D.

Kolmogorov-Arnold Networks

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