8 citations · 9 across the 4 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2026
Uncovering Locally Low-dimensional Structure in Networks by Locally Optimal Spectral Embedding
Hannah Sansford, Nick Whiteley, Patrick Rubin-Delanchy
Standard Adjacency Spectral Embedding (ASE) relies on a global low-rank assumption often incompatible with the sparse, transitive structure of real-world networks, causing local ge…
stat.ML2025★ 1 cited
How high is `high'? Rethinking the roles of dimensionality in topological data analysis and manifold learning
Hannah Sansford, Nick Whiteley, Patrick Rubin-Delanchy
We present a generalised Hanson-Wright inequality and use it to establish new statistical insights into the geometry of data point-clouds. In the setting of a general random functi…