2 citations · 3 across the 6 of their papers we have counts for
8 papers
Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids
Josef Hoppe, Sarra Bouchkati, Farah Nasr +7
Increases in photovoltaic generation, charging of electric vehicles and heat-pump demand challenge operating limits in low-voltage distribution grids. This requires curative curtai…
Faster Inference of Cell Complexes from Flows via Matrix Factorization
Til Spreuer, Josef Hoppe, Michael T. Schaub
We consider the following inference problem: Given a set of edge-flow signals observed on a graph, lift the graph to a cell complex, such that the observed edge-flow signals can be…
Don't be Afraid of Cell Complexes! An Introduction from an Applied Perspective
Josef Hoppe, Vincent P. Grande, Michael T. Schaub
Cell complexes (CCs) are a higher-order network model deeply rooted in algebraic topology that has gained interest in signal processing and network science recently. The processing…
Topological Trajectory Classification and Landmark Inference on Simplicial Complexes
Vincent P. Grande, Josef Hoppe, Florian Frantzen +1
We consider the problem of classifying trajectories on a discrete or discretised 2-dimensional manifold modelled by a simplicial complex. Previous works have proposed to project th…
Random Abstract Cell Complexes
Josef Hoppe, Michael T. Schaub
We define a model for random (abstract) cell complexes (CCs), similiar to the well-known Erdős-Rényi model for graphs and its extensions for simplicial complexes. To build a random…
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains
Mustafa Hajij, Mathilde Papillon, Florian Frantzen +40
We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: h…
Representing Edge Flows on Graphs via Sparse Cell Complexes
Josef Hoppe, Michael T. Schaub
Obtaining sparse, interpretable representations of observable data is crucial in many machine learning and signal processing tasks. For data representing flows along the edges of a…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…