activity
20172020
most citedMachine Learning of Explicit Order Parameters: From the Ising Model to SU(2) Lattice Gauge Theory

146 citations · 148 across the 2 of their papers we have counts for

collaborators

5 papers

cs.NE2020

Logic Guided Genetic Algorithms

Dhananjay Ashok, Joseph Scott, Sebastian Wetzel +2

We present a novel Auxiliary Truth enhanced Genetic Algorithm (GA) that uses logical or mathematical constraints as a means of data augmentation as well as to compute loss (in conj…

physics.comp-ph2020

Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks

Sebastian J. Wetzel, Roger G. Melko, Joseph Scott +2

In this paper, we introduce interpretable Siamese Neural Networks (SNN) for similarity detection to the field of theoretical physics. More precisely, we apply SNNs to events in spe…

physics.comp-ph2019

Spectral Reconstruction with Deep Neural Networks

Lukas Kades, Jan M. Pawlowski, Alexander Rothkopf +5

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. Our a…

cond-mat.str-el20172 cited

Exploring the Hubbard Model on the Square Lattice at Zero Temperature with a Bosonized Functional Renormalization Approach

Sebastian Johann Wetzel

We employ the functional renormalization group to investigate the phase diagram of the Hubbard model on the square lattice with finite chemical potential at zero tempera…

cond-mat.stat-mech2017146 cited

Machine Learning of Explicit Order Parameters: From the Ising Model to SU(2) Lattice Gauge Theory

Sebastian Johann Wetzel, Manuel Scherzer

We present a procedure for reconstructing the decision function of an artificial neural network as a simple function of the input, provided the decision function is sufficiently sy…