Yuichi Ike

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 27

Top Topics

Normalized Maximum Likelihood

Trained Neural Networks

Persistent Homology

Top Venues

Publications

Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
Learning Decision Trees and Forests with Algorithmic Recourse. CoRR (2024)
Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)
Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds. NeurIPS (2023)
Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks. CoRR (2023)
Ryo Yuki, Yuichi Ike, Kenji Yamanishi
Dimensionality selection for hyperbolic embeddings using decomposed normalized maximum likelihood code-length. Knowl. Inf. Syst. 65 (12) (2023)
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
Counterfactual Explanation with Missing Values. CoRR (2023)
Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds. CoRR (2023)
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees. AISTATS (2022)
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. TAG-ML (2022)
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. CoRR (2022)
Ryosuke Masuya, Yuichi Ike, Hiroshi Kera
Vanishing Component Analysis with Contrastive Normalization. CoRR (2022)
Ryo Yuki, Yuichi Ike, Kenji Yamanishi
Dimensionality Selection of Hyperbolic Graph Embeddings using Decomposed Normalized Maximum Likelihood Code-Length. ICDM (2022)
Kohei Ueda, Yuichi Ike, Kenji Yamanishi
Change Detection with Probabilistic Models on Persistence Diagrams. ICDM (2022)
Yasuhiko Asao, Yuichi Ike
Curvature of point clouds through principal component analysis. CoRR (2021)
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs. CoRR (2021)
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs. IJCAI (2021)
Takefumi Hiraki, Tomohiro Hayase, Yuichi Ike, Takashi Tsuboi, Michio Yoshiwaki
Viewpoint Planning of Projector Placement for Spatial Augmented Reality using Star-Kernel Decomposition. VR Workshops (2021)
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
Optimizing persistent homology based functions. ICML (2021)
Martin Royer, Frédéric Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning. AISTATS (2021)
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura
Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization. AAAI (2021)
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura
Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization. CoRR (2020)
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures. AISTATS (2020)
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan
A note on stochastic subgradient descent for persistence-based functionals: convergence and practical aspects. CoRR (2020)
Hirokazu Anai, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hiroya Inakoshi, Raphaël Tinarrage, Yuhei Umeda
DTM-Based Filtrations. SoCG (2019)
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
A General Neural Network Architecture for Persistence Diagrams and Graph Classification. CoRR (2019)
Martin Royer, Frédéric Chazal, Yuichi Ike, Yuhei Umeda
ATOL: Automatic Topologically-Oriented Learning. CoRR (2019)
Hirokazu Anai, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hiroya Inakoshi, Raphaël Tinarrage, Yuhei Umeda
DTM-based filtrations. CoRR (2018)