KANLib -- 一个模块化、可扩展且快速的Kolmogorov-Arnold网络实现
KANLib -- A Modular, Extensible and Fast Kolmogorov-Arnold Network Implementation
AI总结：
提出KANLib框架，通过统一现有KAN实现、支持多种基函数和自适应网格缩放，在保持灵活性和高性能的同时，实现可复现的预测结果。
摘要：
Kolmogorov-Arnold网络（KAN）最近通过用可学习的一元函数替代线性权重，成为传统多层感知器的一种有前途的替代方案。尽管在可解释性和表达能力方面具有理论优势，但由于高计算成本和现有框架中不一致的功能支持，KAN的实际研究仍然困难。本文介绍了KANLib，一个用于开发和评估KAN架构的模块化、可扩展且计算高效的框架。KANLib在强调灵活性、功能一致性和高性能的一致软件架构中，统一了现有实现（包括PyKAN、EfficientKAN和FastKAN）的核心概念。该框架支持两种基函数类型、自适应网格缩放、网格扩展和细粒度架构定制，同时保持与标准PyTorch工作流的兼容性。在加利福尼亚房价基准上的实验评估表明，KANLib在重现已建立参考KAN实现的预测行为的同时，实现了具有竞争力的计算效率。此外，该框架能够探索超出标准KAN公式的架构变体，且对预测性能影响很小。总体而言，KANLib为未来关于可扩展和可扩展KAN架构的研究提供了坚实的基础。
英文摘要：
Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional multilayer perceptrons by replacing linear weights with learnable univariate functions. Despite their theoretical advantages in interpretability and expressiveness, practical research of KANs remains difficult due to high computational costs and inconsistent feature support across existing frameworks. This paper introduces KANLib, a modular, extensible, and computationally efficient framework for developing and evaluating KAN architectures. KANLib unifies core concepts from existing implementations, including PyKAN, EfficientKAN, and FastKAN, within a consistent software architecture that emphasizes flexibility, feature parity, and high performance. The framework supports two basis function types, adaptive grid rescaling, grid extension, and fine-grained architectural customization while maintaining compatibility with standard PyTorch workflows. Experimental evaluation on the California Housing benchmark demonstrates that KANLib reproduces the predictive behavior of established reference KAN implementations while achieving competitive computational efficiency. Furthermore, the framework enables the exploration of architectural variations beyond standard KAN formulations with only minor impacts on predictive performance. Overall, KANLib provides a robust foundation for future research on scalable and extensible KAN architectures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
