Constant-Mean-Curvature Surfaces with Singularities in Minkowski 3-Space. - Yuhei Umeda (Exp. Math., 2009)

Time Series Classification via Topological Data Analysis. - Yuhei Umeda (Inf. Media Technol., 2017)

Simultaneous Optimization of Statistical Model and Control Input Plan. - Yoshinobu Iimura; Masashi Wakaiki; Katsumi Homma; Yuhei Umeda; Junji Kaneko; Hiroyuki Higuchi; Kazumi Kubota; Naoya Asami; Kazuto Ikeda (ACC, 2018)

DTM-Based Filtrations. - Hirokazu Anai; Frédéric Chazal; Marc Glisse; Yuichi Ike; Hiroya Inakoshi; Raphaël Tinarrage; Yuhei Umeda (SoCG, 2019)

A General Neural Network Architecture for Persistence Diagrams and Graph Classification. - Mathieu Carrière; Frédéric Chazal; Yuichi Ike; Théo Lacombe; Martin Royer; Yuhei Umeda (CoRR, 2019)

ATOL: Automatic Topologically-Oriented Learning. - Martin Royer; Frédéric Chazal; Yuichi Ike; Yuhei Umeda (CoRR, 2019)

Topological Data Analysis for Arrhythmia Detection Through Modular Neural Networks. - Meryll Dindin; Yuhei Umeda; Frédéric Chazal (Canadian AI, 2020)

PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures. - Mathieu Carrière; Frédéric Chazal; Yuichi Ike; Théo Lacombe; Martin Royer; Yuhei Umeda (AISTATS, 2020)

ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning. - Martin Royer; Frédéric Chazal; Clément Levrard; Yuhei Umeda; Yuichi Ike (AISTATS, 2021)

Optimizing persistent homology based functions. - Mathieu Carrière; Frédéric Chazal; Marc Glisse; Yuichi Ike; Hariprasad Kannan; Yuhei Umeda (ICML, 2021)

Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs. - Théo Lacombe; Yuichi Ike; Mathieu Carrière; Frédéric Chazal; Marc Glisse; Yuhei Umeda (IJCAI, 2021)

Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics. - Harsh Rangwani; Shrinivas Ramasubramanian; Sho Takemori; Kato Takashi; Yuhei Umeda; Venkatesh Babu R. (NeurIPS, 2022)

Toward Unlimited Self-Learning Monte Carlo with Annealing Process Using VAE's Implicit Isometricity. - Yuma Ichikawa; Akira Nakagawa; Hiromoto Masayuki; Yuhei Umeda (CoRR, 2022)

An Auto-Encoder to Reconstruct Structure with Cryo-EM Images via Theoretically Guaranteed Isometric Latent Space, and Its Application for Automatically Computing the Conformational Pathway. - Kimihiro Yamazaki; Yuichiro Wada; Atsushi Tokuhisa; Mutsuyo Wada; Takashi Katoh; Yuhei Umeda; Yasushi Okuno; Akira Nakagawa (MICCAI (1), 2023)

Improving Predicate Representation in Scene Graph Generation by Self-Supervised Learning. - So Hasegawa; Masayuki Hiromoto; Akira Nakagawa; Yuhei Umeda (WACV, 2023)

Fast and Multi-aspect Mining of Complex Time-stamped Event Streams. - Kota Nakamura; Yasuko Matsubara; Koki Kawabata; Yuhei Umeda; Yuichiro Wada; Yasushi Sakurai (WWW, 2023)

Model-Based Best Arm Identification for Decreasing Bandits. - Sho Takemori; Yuhei Umeda; Aditya Gopalan (AISTATS, 2024)

Deep Mapper: Efficient Visualization of Plausible Conformational Pathways. - Ziyad Oulhaj; Yoshiyuki Ishii; Kento Ohga; Kimihiro Yamazaki; Mutsuyo Wada; Yuhei Umeda; Takashi Katoh; Yuichiro Wada; Hiroaki Kurihara (ECAI, 2024)

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives. - Shrinivas Ramasubramanian; Harsh Rangwani; Sho Takemori; Kunal Samanta; Yuhei Umeda; Venkatesh Babu Radhakrishnan (ICLR, 2024)

Quantum Kernelized Bandits. - Yasunari Hikima; Kazunori Murao; Sho Takemori; Yuhei Umeda (UAI, 2024)