58 citations · 181 across the 8 of their papers we have counts for
8 papers
FORLORN: A Framework for Comparing Offline Methods and Reinforcement Learning for Optimization of RAN Parameters
Vegard Edvardsen, Gard Spreemann, Jeriek Van den Abeele
The growing complexity and capacity demands for mobile networks necessitate innovative techniques for optimizing resource usage. Meanwhile, recent breakthroughs have brought Reinfo…
Simplicial Neural Networks
Stefania Ebli, Michaël Defferrard, Gard Spreemann
We present simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes. These are na…
A Notion of Harmonic Clustering in Simplicial Complexes
Stefania Ebli, Gard Spreemann
We outline a novel clustering scheme for simplicial complexes that produces clusters of simplices in a way that is sensitive to the homology of the complex. The method is inspired…
Same But Different: Distance Correlations Between Topological Summaries
Katharine Turner, Gard Spreemann
Persistent homology allows us to create topological summaries of complex data. In order to analyse these statistically, we need to choose a topological summary and a relevant metri…
Topology of Learning in Artificial Neural Networks
Maxime Gabella
Understanding how neural networks learn remains one of the central challenges in machine learning research. From random at the start of training, the weights of a neural network ev…
Topological exploration of artificial neuronal network dynamics
Jean-Baptiste Bardin, Gard Spreemann, Kathryn Hess
One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, re…
Using persistent homology to reveal hidden information in neural data
Gard Spreemann, Benjamin Dunn, Magnus Bakke Botnan +1
We propose a method, based on persistent homology, to uncover topological properties of a priori unknown covariates of neuron activity. Our input data consist of spike train measur…
Approximating Persistent Homology in Euclidean Space Through Collapses
Magnus Bakke Botnan, Gard Spreemann
The Čech complex is one of the most widely used tools in applied algebraic topology. Unfortunately, due to the inclusive nature of the Čech filtration, the number of simplices grow…