Scalable quantum simulation of continuous-time generative models via tensor networks
The first numerical study of continuous-time flow and diffusion models is presented, in which time-dependent potentials and states are represented as tensor networks, and a coherent amplitude encoding is prepared that can be post-processed by quantum algorithms offering a quadratic advantage over Monte Carlo sampling.
Nathan X. Kodama, L. Wray, S. Cochran et al.
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