Search Results for author: Lukas Kades

Found 4 papers, 0 papers with code

Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning

no code implementations3 Mar 2020 Stefan Bluecher, Lukas Kades, Jan M. Pawlowski, Nils Strodthoff, Julian M. Urban

Machine learning has the potential to aid our understanding of phase structures in lattice quantum field theories through the statistical analysis of Monte Carlo samples.

BIG-bench Machine Learning Representation Learning

Spectral Reconstruction with Deep Neural Networks

no code implementations10 May 2019 Lukas Kades, Jan M. Pawlowski, Alexander Rothkopf, Manuel Scherzer, Julian M. Urban, Sebastian J. Wetzel, Nicolas Wink, Felix P. G. Ziegler

We explore artificial neural networks as a tool for the reconstruction of spectral functions from imaginary time Green's functions, a classic ill-conditioned inverse problem.

Bayesian Inference Spectral Reconstruction

The Discrete Langevin Machine: Bridging the Gap Between Thermodynamic and Neuromorphic Systems

no code implementations16 Jan 2019 Lukas Kades, Jan M. Pawlowski

A formulation of Langevin dynamics for discrete systems is derived as a class of generic stochastic processes.

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