11 citations · 14 across the 5 of their papers we have counts for
3 papers · 1 filter
Learning Minimal Representations of Fermionic Ground States
Felix Frohnert, Emiel Koridon, Stefano Polla
We introduce an unsupervised machine-learning framework that discovers optimally compressed representations of quantum many-body ground states. Using an autoencoder neural network…
Learning Density Functionals from Noisy Quantum Data
Emiel Koridon, Felix Frohnert, Eric Prehn +3
The search for useful applications of noisy intermediate-scale quantum (NISQ) devices in quantum simulation has been hindered by their intrinsic noise and the high costs associated…
Explainable Representation Learning of Small Quantum States
Felix Frohnert, Evert van Nieuwenburg
Unsupervised machine learning models build an internal representation of their training data without the need for explicit human guidance or feature engineering. This learned repre…