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[topoAE++] updated paper references
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ChangeLog.md

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## TTK - ChangeLog
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=
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### dev
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- Cycle-aware dimensionality reduction (TopoAE++)
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- Cycle-aware dimensionality reduction (TopoAE++, IEEE TVCG 2026)
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- Distributed computation of persistent homology! (IEEE TPDS 2025)
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- New backend for TrackingFromFields (critical point based)
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- Fast planar Rips filtration persistence computation

core/base/dimensionReduction/DimensionReduction.h

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///
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/// "Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality
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/// Reduction" \n
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// arXiv preprint, 2025.
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// IEEE Transactions on Visualization and Computer Graphics.
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/// Accepted, to be presented at IEEE VIS 2026.
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#pragma once
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core/base/ripsPersistenceDiagram/FastRipsPersistenceDiagram2.h

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/// \b Related \b publication \n
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/// "Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality
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/// Reduction" \n
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// arXiv preprint, 2025.
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// IEEE Transactions on Visualization and Computer Graphics.
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/// Accepted, to be presented at IEEE VIS 2026.
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#pragma once
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} // namespace ttk::rpd
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#endif
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#endif

core/base/topologicalDimensionReduction/TopologicalDimensionReduction.h

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/// "Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality
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/// Reduction" \n
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// arXiv preprint, 2025.
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/// IEEE Transactions on Visualization and Computer Graphics.
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/// Accepted, to be presented at IEEE VIS 2026.
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///
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/// \sa DimensionReduction.cpp %for a usage example.
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core/vtk/ttkDimensionReduction/ttkDimensionReduction.h

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///
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/// "Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality
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/// Reduction" \n
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// arXiv preprint, 2025.
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/// Mattéo Clémot, Julie Digne, Julien Tierny, \n
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/// IEEE Transactions on Visualization and Computer Graphics.
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/// Accepted, to be presented at IEEE VIS 2026.
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#pragma once
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paraview/xmls/DimensionReduction.xml

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Hariprasad Kannan, Yuhei Umeda,
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38th International Conference on Machine Learning, 2021.
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"Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality Reduction"
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Mattéo Clémot, Julie Digne, Julien Tierny
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arXiv preprint, 2025.
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"Topological Autoencoders++: Fast and Accurate Cycle-Aware Dimensionality Reduction"
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Mattéo Clémot, Julie Digne, Julien Tierny,
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IEEE Transactions on Visualization and Computer Graphics.
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Accepted, to be presented at IEEE VIS 2026.
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</Documentation>
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<InputProperty

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