Data Evolution by Wittgenstein's Rule Following
This paper introduces Wittgenstein's Rule Following (WRF) data evolution, a framework in philomatics for evolving or generating a new dataset from a sequence of previously observed datasets. The method is inspired by Ludwig Wittgenstein's rule-following considerations and his notion of family resemblance in Philosophical Investigations. Unlike standard synthetic data generation, where the goal is usually to sample from or augment a fixed distribution, WRF aims to continue the implicit rule expressed by a historical sequence of datasets while preserving resemblance to the previous datasets. WRF represents each dataset by structural descriptors rather than pointwise correspondences. These d...
| Authors | Aydin Ghojogh, Benyamin Ghojogh |
|---|---|
| Primary category | stat.ML |
| Published | 21 June 2026 |
| Last updated at source | 21 June 2026 |
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