1 citations · 1 across the 2 of their papers we have counts for
3 papers
Physics Inspired Neural Networks Enable Efficient Graph Coloring
Lorenzo Colantonio, Andrea Cacioppo, Federico Scarpati +3
Combinatorial optimization problems near algorithmic phase transitions represent a fundamental challenge for both classical algorithms and machine learning approaches. Among them,…
Quantum Diffusion Models
Andrea Cacioppo, Lorenzo Colantonio, Simone Bordoni +1
We propose a quantum version of a generative diffusion model. In this algorithm, artificial neural networks are replaced with parameterized quantum circuits, in order to directly g…
Compound Channel Capacities under Energy Constraints and Application
Andrea Cacioppo, Janis Nötzel, Matteo Rosati
Compound channel models offer a simple and straightforward way of analyzing the stability of decoder design under model variations. With this work we provide a coding theorem for a…