Yuichi Ike

31 papers A* 8A 3Journal 17Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning Tangent Bundles and Characteristic Classes with Autoencoder Atlases.
CoRR
Eduardo Paluzo-Hidalgo, Yuichi Ike
2026 J jnl
Persistence-based topological optimization: a survey.
CoRR
Mathieu Carrière, Yuichi Ike, Théo Lacombe, Naoki Nishikawa
2024 — conf
Distribution-Aligned Sequential Counterfactual Explanation with Local Outlier Factor.
PRICAI (1)
Shoki Yamao, Ken Kobayashi, Kentaro Kanamori, Takuya Takagi, Yuichi Ike, Kazuhide Nakata
2024 A* conf
Learning Decision Trees and Forests with Algorithmic Recourse.
ICML
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
2024 J jnl
Learning Decision Trees and Forests with Algorithmic Recourse.
CoRR
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
2024 J jnl
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks.
Trans. Mach. Learn. Res.
Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2023 A* conf
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds.
NeurIPS
Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi
2023 J jnl
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds.
CoRR
Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi
2023 J jnl
Counterfactual Explanation with Missing Values.
CoRR
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
2023 J jnl
Dimensionality selection for hyperbolic embeddings using decomposed normalized maximum likelihood code-length.
Knowl. Inf. Syst.
Ryo Yuki, Yuichi Ike, Kenji Yamanishi
2023 J jnl
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks.
CoRR
Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2022 A* conf
Change Detection with Probabilistic Models on Persistence Diagrams.
ICDM
Kohei Ueda, Yuichi Ike, Kenji Yamanishi
2022 A conf
Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees.
AISTATS
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
2022 A* conf
Dimensionality Selection of Hyperbolic Graph Embeddings using Decomposed Normalized Maximum Likelihood Code-Length.
ICDM
Ryo Yuki, Yuichi Ike, Kenji Yamanishi
2022 — conf
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds.
TAG-ML
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2022 J jnl
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds.
CoRR
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2022 J jnl
Vanishing Component Analysis with Contrastive Normalization.
CoRR
Ryosuke Masuya, Yuichi Ike, Hiroshi Kera
2021 A conf
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning.
AISTATS
Martin Royer, Frédéric Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike
2021 J jnl
Curvature of point clouds through principal component analysis.
CoRR
Yasuhiko Asao, Yuichi Ike
2021 A* conf
Optimizing persistent homology based functions.
ICML
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
2021 A* conf
Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization.
AAAI
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura
2021 A* conf
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs.
IJCAI
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021 J jnl
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs.
CoRR
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021 — conf
Viewpoint Planning of Projector Placement for Spatial Augmented Reality using Star-Kernel Decomposition.
VR Workshops
Takefumi Hiraki, Tomohiro Hayase, Yuichi Ike, Takashi Tsuboi, Michio Yoshiwaki
2020 J jnl
A note on stochastic subgradient descent for persistence-based functionals: convergence and practical aspects.
CoRR
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan
2020 J jnl
Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization.
CoRR
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura
2020 A conf
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures.
AISTATS
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2019 J jnl
A General Neural Network Architecture for Persistence Diagrams and Graph Classification.
CoRR
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2019 J jnl
ATOL: Automatic Topologically-Oriented Learning.
CoRR
Martin Royer, Frédéric Chazal, Yuichi Ike, Yuhei Umeda
2019 A* conf
DTM-Based Filtrations.
SoCG
Hirokazu Anai, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hiroya Inakoshi, Raphaël Tinarrage, Yuhei Umeda
2018 J jnl
DTM-based filtrations.
CoRR
Hirokazu Anai, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hiroya Inakoshi, Raphaël Tinarrage, Yuhei Umeda