1 code implementation • 21 Jun 2022 • Renata Turkeš, Guido Montúfar, Nina Otter
The goal of this work is to identify some types of problems where PH performs well or even better than other methods in data analysis.
1 code implementation • NeurIPS 2021 • Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael Bronstein
Nevertheless, these models can be severely constrained by the rigid combinatorial structure of Simplicial Complexes (SCs).
Ranked #1 on Graph Regression on ZINC 100k
1 code implementation • ICLR Workshop GTRL 2021 • Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael Bronstein
The pairwise interaction paradigm of graph machine learning has predominantly governed the modelling of relational systems.
no code implementations • NeurIPS Workshop TDA_and_Beyond 2020 • Guido Montúfar, Nina Otter, Yuguang Wang
Topological data analysis uses tools from topology -- the mathematical area that studies shapes -- to create representations of data.
no code implementations • 24 Aug 2017 • Heather A. Harrington, Nina Otter, Hal Schenck, Ulrike Tillmann
A fundamental tool in topological data analysis is persistent homology, which allows extraction of information from complex datasets in a robust way.
Algebraic Topology Commutative Algebra 55B55, 68U05, 68Q17, 13P25 (primary)
1 code implementation • 30 Jun 2015 • Nina Otter, Mason A. Porter, Ulrike Tillmann, Peter Grindrod, Heather A. Harrington
We give a friendly introduction to PH, navigate the pipeline for the computation of PH with an eye towards applications, and use a range of synthetic and real-world data sets to evaluate currently available open-source implementations for the computation of PH.
Algebraic Topology Computational Geometry Data Analysis, Statistics and Probability Quantitative Methods