217 citations · 333 across the 6 of their papers we have counts for
4 papers · 1 filter
Quantum-inspired memory-enhanced stochastic algorithms
John Realpe-Gómez, Nathan Killoran
Stochastic models are highly relevant tools in science, engineering, and society. Recent work suggests emerging quantum computing technologies can substantially decrease the memory…
Modeling observers as physical systems representing the world from within: Quantum theory as a physical and self-referential theory of inference
John Realpe-Gómez
In 1929 Szilard pointed out that the physics of the observer may play a role in the analysis of experiments. The same year, Bohr pointed out that complementarity appears to arise n…
Quantum-Assisted Learning of Hardware-Embedded Probabilistic Graphical Models
Marcello Benedetti, John Realpe-Gómez, Rupak Biswas +1
Mainstream machine-learning techniques such as deep learning and probabilistic programming rely heavily on sampling from generally intractable probability distributions. There is i…
Estimation of effective temperatures in quantum annealers for sampling applications: A case study with possible applications in deep learning
Marcello Benedetti, John Realpe-Gómez, Rupak Biswas +1
An increase in the efficiency of sampling from Boltzmann distributions would have a significant impact on deep learning and other machine-learning applications. Recently, quantum a…