5.7k citations · 20.9k across the 136 of their papers we have counts for
137 papers
Fully Non-Linear Neuromorphic Computing with Linear Wave Scattering
Clara C. Wanjura, Florian Marquardt
The increasing complexity of neural networks and the energy consumption associated with training and inference create a need for alternative neuromorphic approaches, e.g. using opt…
Deep Bayesian Experimental Design for Quantum Many-Body Systems
Leopoldo Sarra, Florian Marquardt
Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent dev…
Discovering Quantum Circuit Components with Program Synthesis
Leopoldo Sarra, Kevin Ellis, Florian Marquardt
Despite rapid progress in the field, it is still challenging to discover new ways to take advantage of quantum computation: all quantum algorithms need to be designed by hand, and…
Deep learning of spatial densities in inhomogeneous correlated quantum systems
Alex Blania, Sandro Herbig, Fabian Dechent +2
Machine learning has made important headway in helping to improve the treatment of quantum many-body systems. A domain of particular relevance are correlated inhomogeneous systems.…
Realizing a deep reinforcement learning agent discovering real-time feedback control strategies for a quantum system
Kevin Reuer, Jonas Landgraf, Thomas Fösel +10
To realize the full potential of quantum technologies, finding good strategies to control quantum information processing devices in real time becomes increasingly important. Usuall…
Investigation of inverse design of multilayer thin-films with conditional invertible Neural Networks
Alexander Luce, Ali Mahdavi, Heribert Wankerl +1
The task of designing optical multilayer thin-films regarding a given target is currently solved using gradient-based optimization in conjunction with methods that can introduce ad…