Search Results for author:
Found 4 papers, 1 papers with code
Beyond the noise: intrinsic dimension estimation with optimal neighbourhood identification
The Intrinsic Dimension (ID) is a key concept in unsupervised learning and feature selection, as it is a lower bound to the number of variables which are necessary to describe a system.
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
A language model (LM) is a mapping from a linguistic context to an output token.
Intrinsic dimension estimation for discrete metrics
Real world-datasets characterized by discrete features are ubiquitous: from categorical surveys to clinical questionnaires, from unweighted networks to DNA sequences.
DADApy: Distance-based Analysis of DAta-manifolds in Python
DADApy is a python software package for analysing and characterising high-dimensional data manifolds.
