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20242026
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cs.LG2026

Differentiable Lifting for Topological Neural Networks

Jorge Luiz Franco, Gabriel Duarte, Alexander Nikitin +3

Topological neural networks (TNNs) enable leveraging high-order structures on graphs (e.g., cycles and cliques) to boost the expressive power of message-passing neural networks. In…

cs.LG2025

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…

cs.LG2024

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…

cs.LG2024

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…

cs.LG2024

TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series

Alexander Nikitin, Letizia Iannucci, Samuel Kaski

Temporally indexed data are essential in a wide range of fields and of interest to machine learning researchers. Time series data, however, are often scarce or highly sensitive, wh…