Ike, Yuichi

11 publications

ICML 2024 Learning Decision Trees and Forests with Algorithmic Recourse Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike

TMLR 2024 MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frederic Chazal

NeurIPS 2023 Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds Naoki Nishikawa, Yuichi Ike, Kenji Yamanishi

AISTATS 2022 Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike

ICLRW 2022 RipsNet: A General Architecture for Fast and Robust Estimation of the Persistent Homology of Point Clouds Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frederic Chazal

AISTATS 2021 ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning Martin Royer, Frederic Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike

ICML 2021 Optimizing Persistent Homology Based Functions Mathieu Carriere, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda

AAAI 2021 Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura

IJCAI 2021 Topological Uncertainty: Monitoring Trained Neural Networks Through Persistence of Activation Graphs Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda

NeurIPSW 2020 Application of Topological Data Analysis to Delirium Detection Mari Kajitani, Ken Kobayashi, Yuichi Ike, Takehiko Yamanashi, Yuhei Umeda, Yoshimasa Kadooka, Gen Shinozaki

AISTATS 2020 PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures Mathieu Carriere, Frederic Chazal, Yuichi Ike, Theo Lacombe, Martin Royer, Yuhei Umeda