Data Evolution by Wittgenstein's Rule Following

arXiv:2606.22674 · stat.ML, cs.AI, cs.LG · Submitted 2026-06-21 · Read on arXiv

Aydin Ghojogh, Benyamin Ghojogh

stat.ML, cs.AI, cs.LG

Submitted: 2026-06-21

Code: https://github.com/aghojogh/WRF_

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Clustering — 15× in this paper · explained in 2 episodes
• Class Imbalance — 6× in this paper · explained in 3 episodes
• Adam — 4× in this paper · explained in 3 episodes
• Augmentation — 4× in this paper · explained in 2 episodes
• Concept Drift — 4× in this paper · explained in 6 episodes
• Data Augmentation — 4× in this paper · explained in 10 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Anisotropy — 3× in this paper · explained in 4 episodes
• Synthetic Data Generation — 3× in this paper · explained in 5 episodes
• Dimensionality Reduction — 2× in this paper · explained in 2 episodes
• Generator — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Principal Component Analysis — 2× in this paper
• Regularization — 2× in this paper · explained in 3 episodes
• Structural Properties — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Continual Learning — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 10 episodes
• Diffusion Models — 1× in this paper · explained in 9 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Generative Data Augmentation — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• K-means Clustering — 1× in this paper · explained in 3 episodes
• Normalizing Flow — 1× in this paper · explained in 4 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Principal Component Analysis (PCA) — 1× in this paper · explained in 8 episodes
• Quantization — 1× in this paper · explained in 15 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Wittgenstein's Family Resemblance Clustering Algorithm
• A Unified Framework for Generative Data Augmentation: A Comprehensive Survey
• Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A Human
• On Philomatics and Psychomatics for Combining Philosophy and Psychology with Mathematics
• Adam: A Method for Stochastic Optimization
• Auto-Encoding Variational Bayes
• Witgenstein's influence on artificial intelligence

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