Learning and Inference in Hilbert Space with Quantum Graphical Models.

Siddarth Srinivasan
Siddarth Srinivasan

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018): 10338-10347

Cited by: 8|Views9
EI

Abstract:

Quantum Graphical Models (QGMs) generalize classical graphical models by adopting the formalism for reasoning about uncertainty from quantum mechanics. Unlike classical graphical models, QGMs represent uncertainty with density matrices in complex Hilbert spaces. Hilbert space embeddings (HSEs) also generalize Bayesian inference in Hilbert...More

Code:

Data:

ZH
Your rating :
0

 

Tags
Comments