Philosophical Thoughts on Kolmogorov-Arnold Networks
6 days ago
- #neural networks
- #philosophy of science
- #machine learning
- Kolmogorov-Arnold Networks (KANs) are a new type of neural networks proposed by the author and collaborators, differing from Multi-Layer Perceptrons (MLPs).
- KANs and MLPs have the same expressive power but differ in emergent properties like optimization, generalization, and interpretability.
- Philosophically, MLPs align with holism ('more is different'), while KANs align with reductionism (complex 'atoms' but simple combinations).
- KANs are more aligned with scientific thinking, which traditionally follows reductionism, making them promising for scientific tasks.
- MLPs excel in non-scientific tasks like vision and language, whereas KANs are better suited for tasks requiring symbolic formula compilation.
- The author emphasizes the importance of empirical experiments alongside philosophical reasoning to understand KANs and MLPs fully.