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cs.LG2026
Topological Deep Learning Challenge 2026: Bridging the Gap
Guillermo Bernárdez, Lev Telyatnikov, Mathilde Papillon +68
This paper describes the 2026 edition of the Topological Deep Learning Challenge: Bridging the Gap, hosted at the second Topology, Algebra, and Geometry in Data Science (TAG-DS) Co…
cs.LG2026
CAESAR: Clustering via Autonomous Embedding-Space Agglomerative Reorganization
Ilan Bacry, Rémi Devaux, Antoine Jardin
Clustering algorithms that operate on nearest-neighbor graphs, such as FINCH (First Integer Neighbor Clustering Hierarchy), depend heavily on the quality of the embedding space the…
cs.LG2026
Look Before You Lift: Visual and Quantitative Diagnostics for Topological Deep Learning
Mathilde Papillon, Guillermo Bernárdez, Álvaro Ballón Barreiro +4
Topological deep learning (TDL) methods rely on lifting raw data into higher-order discrete domains such as simplicial complexes, cell complexes, and hypergraphs. In practice, this…