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Vanishing Component Analysis with Contrastive Normalization


Oct 27, 2022
Ryosuke Masuya, Yuichi Ike, Hiroshi Kera

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* 22pages, 1 figure 

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RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds


Feb 04, 2022
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal

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* 23 pages, 4 figures 

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Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs


May 07, 2021
Théo Lacombe, Yuichi Ike, Mathieu Carriere, Frédéric Chazal, Marc Glisse, Yuhei Umeda

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* 2021 International Joint Conference on Artificial Intelligence, Aug 2021, Montr{\'e}al, Canada 

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Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization


Dec 22, 2020
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura

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* 20 pages, 5 figures, to appear in the 35th AAAI Conference on Artificial Intelligence (#AAAI2021) 

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ATOL: Automatic Topologically-Oriented Learning


Sep 30, 2019
Martin Royer, Frédéric Chazal, Yuichi Ike, Yuhei Umeda

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PersLay: A Simple and Versatile Neural Network Layer for Persistence Diagrams


Jun 05, 2019
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda

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A General Neural Network Architecture for Persistence Diagrams and Graph Classification


Apr 20, 2019
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda

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