activity
20222025
most citedGraph-Time Convolutional Neural Networks: Architecture and Theoretical Analysis

7 citations · 13 across the 8 of their papers we have counts for

collaborators

8 papers

eess.SP2025

Graph signal aware decomposition of dynamic networks via latent graphs

Bishwadeep Das, Andrei Buciulea, Antonio G. Marques +1

Dynamics on and of networks refer to changes in topology and node-associated signals, respectively and are pervasive in many socio-technological systems, including social, biologic…

stat.ML2025

Matched Topological Subspace Detector

Chengen Liu, Victor M. Tenorio, Antonio G. Marques +1

Topological spaces, represented by simplicial complexes, capture richer relationships than graphs by modeling interactions not only between nodes but also among higher-order entiti…

cs.IR2025

Towards Carbon Footprint-Aware Recommender Systems for Greener Item Recommendation

Raoul Kalisvaart, Masoud Mansoury, Alan Hanjalic +1

The commodity and widespread use of online shopping are having an unprecedented impact on climate, with emission figures from key actors that are easily comparable to those of a la…

eess.SP2024

Topological Signal Processing and Learning: Recent Advances and Future Challenges

Elvin Isufi, Geert Leus, Baltasar Beferull-Lozano +2

Developing methods to process irregularly structured data is crucial in applications like gene-regulatory, brain, power, and socioeconomic networks. Graphs have been the go-to alge…

cs.LG2023

Hodge-Aware Contrastive Learning

Alexander Möllers, Alexander Immer, Vincent Fortuin +1

Simplicial complexes prove effective in modeling data with multiway dependencies, such as data defined along the edges of networks or within other higher-order structures. Their sp…

cs.LG20236 cited

Convolutional Learning on Simplicial Complexes

Maosheng Yang, Elvin Isufi

We propose a simplicial complex convolutional neural network (SCCNN) to learn data representations on simplicial complexes. It performs convolutions based on the multi-hop simplici…