3 papers
stat.ML2026
The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours
Robert Allison, Tomasz Maciazek, Anthony Stephenson
Gaussian process () regression is a widely used non-parametric modeling tool, but its cubic complexity in the training size limits its use on massive data sets. A practical rem…
quant-ph2025
A toolbox of spin-adapted generalized Pauli constraints
Julia Liebert, Yannick Lemke, Murat Altunbulak +3
We establish a toolbox for studying and applying spin-adapted generalized Pauli constraints (GPCs) in few-electron quantum systems. By exploiting the spin symmetry of realistic …
quant-ph2024
Solving one-body ensemble N-representability problems with spin
Julia Liebert, Federico Castillo, Jean-Philippe Labbé +2
The Pauli exclusion principle is fundamental to understanding electronic quantum systems. It namely constrains the expected occupancies of orbitals according to $0 \leq…