3 papers
quant-ph2026
Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks
Marcel Mordarski, Nathan Mani, Arshad Patel +2
Encrypted training relies on keeping server-side updates low-degree. This constraint traditionally excludes models whose weights inhabit a compact Lie group (notably variational qu…
cs.IT2025
Simple physical systems as a reference for multivariate information dynamics
Alberto Liardi, Madalina I. Sas, George Blackburne +3
Understanding a complex system entails capturing the non-trivial collective phenomena that arise from interactions between its different parts. Information theory is a flexible and…
cs.LG2024
A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks
Edward Pearce-Crump, William J. Knottenbelt
Group equivariant neural networks are growing in importance owing to their ability to generalise well in applications where the data has known underlying symmetries. Recent charact…