3 papers
cs.LG2025
Atlas-based Manifold Representations for Interpretable Riemannian Machine Learning
Ryan A. Robinett, Sophia A. Madejski, Kyle Ruark +2
Despite the popularity of the manifold hypothesis, current manifold-learning methods do not support machine learning directly on the latent -dimensional data manifold, as they p…
quant-ph2025
Toward Quantum-Enabled Biomarker Discovery: An Outlook from Q4Bio
Dhirpal Shah, Mariesa Teo, Ryan A. Robinett +12
We present a case study and forward-looking perspective on co-design for hybrid quantum-classical algorithms, centered on the goal of empirical quantum advantage (EQA), which we de…
cs.LG2025
Manifold learning and optimization using tangent space proxies
Ryan A. Robinett, Lorenzo Orecchia, Samantha J. Riesenfeld
We present a framework for efficiently approximating differential-geometric primitives on arbitrary manifolds via construction of an atlas graph representation, which leverages the…