14 citations · 14 across the 5 of their papers we have counts for
6 papers
Hyperbolic Latent Space Models for Network Embedding: Model Specification and Bayesian Inference
Yiwei Gong, Anna L. Smith, Dena Asta +1
Many real-world networks exhibit hierarchical, tree-like structure and heavy-tailed degree distributions, phenomena not readily captured by standard statistical models for network…
Lower Bounds for Kernel Density Estimation on Symmetric Spaces
Dena Marie Asta
We prove that kernel density estimation on symmetric spaces of non-compact type, whose L2-risk was bounded above in previous work (Asta,2021), in fact achieves a minimax rate of co…
Non-Parametric Manifold Learning
Dena Marie Asta
We introduce an estimator for distances in a compact Riemannian manifold based on graph Laplacian estimates of the Laplace-Beltrami operator. We upper bound the error in the estima…
The Geometry of Continuous Latent Space Models for Network Data
Anna L. Smith, Dena M. Asta, Catherine A. Calder
We review the class of continuous latent space (statistical) models for network data, paying particular attention to the role of the geometry of the latent space. In these models,…
Geometric Network Comparison
Dena Asta, Cosma Rohilla Shalizi
Network analysis has a crucial need for tools to compare networks and assess the significance of differences between networks. We propose a principled statistical approach to netwo…
Kernel Density Estimation on Symmetric Spaces of Non-Compact Type
Dena Marie Asta
We construct a kernel density estimator on symmetric spaces of non-compact type and establish an upper bound for its convergence rate, analogous to the minimax rate for classical k…