20 citations · 24 across the 4 of their papers we have counts for
4 papers
Untapped Potential in Self-Optimization of Hopfield Networks: The Creativity of Unsupervised Learning
Natalya Weber, Christian Guckelsberger, Tom Froese
The Self-Optimization (SO) model can be considered as the third operational mode of the classical Hopfield Network, leveraging the power of associative memory to enhance optimizati…
On the use of associative memory in Hopfield networks designed to solve propositional satisfiability problems
Natalya Weber, Werner Koch, Ozan Erdem +1
Hopfield networks are an attractive choice for solving many types of computational problems because they provide a biologically plausible mechanism. The Self-Optimization (SO) mode…
Scaling up the self-optimization model by means of on-the-fly computation of weights
Natalya Weber, Werner Koch, Tom Froese
The Self-Optimization (SO) model is a useful computational model for investigating self-organization in "soft" Artificial life (ALife) as it has been shown to be general enough to…
Deep learning based quantum vortex detection in atomic Bose-Einstein condensates
Friederike Metz, Juan Polo, Natalya Weber +1
Quantum vortices naturally emerge in rotating Bose-Einstein condensates (BECs) and, similarly to their classical counterparts, allow the study of a range of interesting out-of-equi…