Kolmogorov-Arnold Networks: A More Scientific Neural Network?
2025-08-22
This blog post explores the philosophical differences between Kolmogorov-Arnold Networks (KANs) and Multi-Layer Perceptrons (MLPs). While acknowledging their equal expressive power, the author argues that differences emerge in optimization, generalization, and interpretability. KANs align more with reductionism, while MLPs lean towards holism. The author suggests that KANs might be better suited for modeling scientific phenomena, given science's reliance on reductionist approaches, citing the example of compiling symbolic formulas. However, the importance of empirical experiments is stressed, acknowledging potential weaknesses of KANs in non-scientific tasks.
AI
reductionism