3 citations · 3 across the 7 of their papers we have counts for
7 papers
Persistence-based topological optimization: a survey
Mathieu Carriere, Yuichi Ike, Théo Lacombe +1
Computational topology provides a tool, persistent homology, to extract quantitative descriptors from structured objects (images, graphs, point clouds, etc). These descriptors can…
Learning Tangent Bundles and Characteristic Classes with Autoencoder Atlases
Eduardo Paluzo-Hidalgo, Yuichi Ike
We introduce a theoretical framework that connects multi-chart autoencoders in manifold learning with the classical theory of vector bundles and characteristic classes. Rather than…
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds
Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi
Machine learning for point clouds has been attracting much attention, with many applications in various fields, such as shape recognition and material science. For enhancing the ac…
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Charles Arnal, Felix Hensel, Mathieu Carrière +4
Despite their successful application to a variety of tasks, neural networks remain limited, like other machine learning methods, by their sensitivity to shifts in the data: their p…
Vanishing Component Analysis with Contrastive Normalization
Ryosuke Masuya, Yuichi Ike, Hiroshi Kera
Vanishing component analysis (VCA) computes approximate generators of vanishing ideals of samples, which are further used for extracting nonlinear features of the samples. Recent s…
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frédéric Chazal, Clément Levrard +2
Robust topological information commonly comes in the form of a set of persistence diagrams, finite measures that are in nature uneasy to affix to generic machine learning framework…
Hyperbolic localization via shrinking subbundles
Yuichi Ike
We study the Lefschetz fixed point formula for constructible sheaves with higher-dimensional fixed point sets. We give another proof to the explicit description of Lefschetz cycles…