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We introduce giotto-tda, a Python library that integrates high-performance topological data analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ implementations.
Topology and data
Gunnar Carlsson · 2009
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Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival
Monica Nicolau, Arnold J. Levine, and Gunnar Carlsson · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, et al · 2011
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, et al · 2015
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A stable multi-scale kernel for topological machine learning
J. Reininghaus, S. Huber, U. Bauer, and R. Kwitt · 2015
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Comparing persistence diagrams through complex vectors
Barbara Di Fabio and Massimo Ferri · 2015
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Stable topological signatures for points on 3d shapes
Mathieu Carrière, Steve Y. Oudot, and Maks Ovsjanikov · 2015
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Persistence weighted Gaussian kernel for topological data analysis
Genki Kusano, Yasuaki Hiraoka, and Kenji Fukumizu · 2016
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Cliques of neurons bound into cavities provide a missing link between structure and function
Michael W. Reimann, Max Nolte, Martina Scolamiero, et al · 2017
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skorch: A scikit-learn compatible neural network library that wraps PyTorch , 2017
Marian Tietz, Thomas J. Fan, Daniel Nouri, Benjamin Bossan, and skorch Developers · 2017
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Sliced Wasserstein kernel for persistence diagrams
Mathieu Carrière, Marco Cuturi, and Steve Oudot · 2017
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Geometry helps to compare persistence diagrams
Michael Kerber, Dmitriy Morozov, and Arnur Nigmetov · 2017
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pybind11 – seamless operability between C++11 and Python, 2017
Wenzel Jakob, Jason Rhinelander, and Dean Moldovan · 2017
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High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites
Yongjin Lee, Senja D Barthel, Paweł Dłotko, et al · 2018
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Persistence Fisher kernel: A Riemannian manifold kernel for persistence diagrams
Tam Le and Makoto Yamada · 2018
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Ripser.py: A lean persistent homology library for Python
Christopher Tralie, Nathaniel Saul, and Rann Bar-On · 2018
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Dionysus 2 – library for computing persistent homology, 2018
Dmitriy Morozov · 2018
Consistent manifold representation for topological data analysis
Tyrus Berry and Timothy Sauer · 2019
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Ripser: efficient computation of vietoris-rips persistence barcodes
Ulrich Bauer · 2019
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Scikit-TDA: Topological data analysis for Python, 2019
Nathaniel Saul and Chris Tralie · 2019
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An introduction to topological data analysis for physicists: From LGM to FRBs
Jeff Murugan and Duncan Robertson · 2019
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Kepler Mapper: A flexible Python implementation of the Mapper algorithm
Hendrik van Veen, Nathaniel Saul, David Eargle, et al · 2019
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Exposition and interpretation of the topology of neural networks
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Topological times series analysis
Jose A. Perea · 2019
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Persistent homology of complex networks for dynamic state detection
Audun Myers, Elizabeth Munch, and Firas A. Khasawneh · 2019
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GUDHI User and Reference Manual
The GUDHI Project · 2020
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