22 citations · 61 across the 30 of their papers we have counts for
9 papers · 1 filter
Towards a Health-Based Power Grid Optimization in the Artificial Intelligence Era
Claudio Battiloro, Gianluca Guidi, Falco J. Bargagli-Stoffi +1
The electric power sector is one of the largest contributors to greenhouse gas emissions in the world. In recent years, there has been an unprecedented increase in electricity dema…
TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon, Guillermo Bernárdez, Claudio Battiloro +1
Graph Neural Networks (GNNs) effectively learn from relational data by leveraging graph symmetries. However, many real-world systems -- such as biological or social networks -- fea…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
Higher-Order Topological Directionality and Directed Simplicial Neural Networks
Manuel Lecha, Andrea Cavallo, Francesca Dominici +2
Topological Deep Learning (TDL) has emerged as a paradigm to process and learn from signals defined on higher-order combinatorial topological spaces, such as simplicial or cell com…
TopoBench: A Framework for Benchmarking Topological Deep Learning
Lev Telyatnikov, Guillermo Bernardez, Marco Montagna +34
This work introduces TopoBench, an open-source library designed to standardize benchmarking and accelerate research in topological deep learning (TDL). TopoBench decomposes TDL int…
Attending to Topological Spaces: The Cellular Transformer
Rubén Ballester, Pablo Hernández-García, Mathilde Papillon +6
Topological Deep Learning seeks to enhance the predictive performance of neural network models by harnessing topological structures in input data. Topological neural networks opera…
E(n) Equivariant Topological Neural Networks
Claudio Battiloro, Ege Karaismailoğlu, Mauricio Tec +3
Graph neural networks excel at modeling pairwise interactions, but they cannot flexibly accommodate higher-order interactions and features. Topological deep learning (TDL) has emer…
Dynamic Relative Representations for Goal-Oriented Semantic Communications
Simone Fiorellino, Claudio Battiloro, Emilio Calvanese Strinati +1
In future 6G wireless networks, semantic and effectiveness aspects of communications will play a fundamental role, incorporating meaning and relevance into transmissions. However,…
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…