most citedConditional Generative Models for Learning Stochastic Processes

2 citations · 3 across the 5 of their papers we have counts for

collaborators
Showing quant-phShow all

3 papers · 1 filter

quant-ph2026

Assessing the Practical Feasibility of the Clader-Jacobs-Sprouse Quantum Algorithm for Calculating Radar Cross Sections

Edward Parker, Nicholas A. O'Donoughue, Alvin Moon +1

In 2013, Clader, Jacobs, and Sprouse developed a quantum computing algorithm that solves electromagnetic scattering problems exponentially faster than the best known classical algo…

quant-ph2023

Efficient quantum loading of probability distributions through Feynman propagators

Elie Alhajjar, Jesse Geneson, Anupam Prakash +1

We present quantum algorithms for the loading of probability distributions using Hamiltonian simulation for one dimensional Hamiltonians of the form .…

quant-ph2023★ 2 cited

Conditional Generative Models for Learning Stochastic Processes

Salvatore Certo, Anh Pham, Nicolas Robles +1

A framework to learn a multi-modal distribution is proposed, denoted as the Conditional Quantum Generative Adversarial Network (C-qGAN). The neural network structure is strictly wi…