Multiple Nonlinear Subspace Methods Using Subspace-based Support Vector Machines. - Takuya Kitamura; Shigeo Abe; Yusuke Tanaka 002 (ICMLA (1), 2011)

Inferring Latent Triggers of Purchases with Consideration of Social Effects and Media Advertisements. - Yusuke Tanaka 002; Takeshi Kurashima; Yasuhiro Fujiwara; Tomoharu Iwata; Hiroshi Sawada (WSDM, 2016)

Estimating Latent People Flow without Tracking Individuals. - Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda; Naonori Ueda (IJCAI, 2018)

Improving Route Traffic Estimation by Considering Staying Population. - Hitoshi Shimizu; Tatsushi Matsubayashi; Yusuke Tanaka 002; Tomoharu Iwata; Naonori Ueda; Hiroshi Sawada (PRIMA, 2018)

Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. - Yusuke Tanaka 002; Tomoharu Iwata; Toshiyuki Tanaka; Takeshi Kurashima; Maya Okawa; Hiroyuki Toda (AAAI, 2019)

Predicting Traffic Accidents with Event Recorder Data. - Yoshiaki Takimoto; Yusuke Tanaka 002; Takeshi Kurashima; Shuhei Yamamoto; Maya Okawa; Hiroyuki Toda (PredictGIS@SIGSPATIAL, 2019)

Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. - Maya Okawa; Tomoharu Iwata; Takeshi Kurashima; Yusuke Tanaka 002; Hiroyuki Toda; Naonori Ueda (KDD, 2019)

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs. - Yusuke Tanaka 002; Toshiyuki Tanaka; Tomoharu Iwata; Takeshi Kurashima; Maya Okawa; Yasunori Akagi; Hiroyuki Toda (NeurIPS, 2019)

Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems. - Maya Okawa; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Tomohiro Yamada (IEICE Trans. Inf. Syst., 2019)

Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm. - Yasunori Akagi; Takuya Nishimura 002; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda (AAAI, 2020)

Probabilistic Optimal Transport based on Collective Graphical Models. - Yasunori Akagi; Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda (CoRR, 2020)

Few-shot Learning for Spatial Regression. - Tomoharu Iwata; Yusuke Tanaka 002 (CoRR, 2020)

Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima (KDD, 2021)

Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations. - Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda; Naonori Ueda; Toshiyuki Tanaka (Artif. Intell., 2021)

Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data. - Yusuke Tanaka 002; Tomoharu Iwata; Naonori Ueda (NeurIPS, 2022)

Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains. - Yusuke Tanaka 002; Toshiyuki Tanaka; Tomoharu Iwata; Takeshi Kurashima; Maya Okawa; Yasunori Akagi; Hiroyuki Toda (CoRR, 2022)

Few-shot learning for spatial regression via neural embedding-based Gaussian processes. - Tomoharu Iwata; Yusuke Tanaka 002 (Mach. Learn., 2022)

Context-aware spatio-temporal event prediction via convolutional Hawkes processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Hisashi Kashima (Mach. Learn., 2022)

Meta-learning of Physics-informed Neural Networks for Efficiently Solving Newly Given PDEs. - Tomoharu Iwata; Yusuke Tanaka 002; Naonori Ueda (CoRR, 2023)

Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics. - Tomoharu Iwata; Yusuke Tanaka 002 (IJCAI, 2024)

Meta-Learning for Neural Network-based Temporal Point Processes. - Yoshiaki Takimoto; Yusuke Tanaka 002; Tomoharu Iwata; Maya Okawa; Hideaki Kim; Hiroyuki Toda; Takeshi Kurashima (CoRR, 2024)

Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs. - Yusuke Tanaka 002; Takaharu Yaguchi; Tomoharu Iwata; Naonori Ueda (CoRR, 2024)

Meta-Learning under Task Shift. - Lei Sun; Yusuke Tanaka 002; Tomoharu Iwata (Trans. Mach. Learn. Res., 2024)

Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations. - Yusuke Tanaka 002; Takaharu Yaguchi; Tomoharu Iwata; Naonori Ueda (AISTATS, 2025)

Meta-Learning for Graphs with Heterogeneous Node Attribute Spaces for Few-Shot Edge Predictions. - Zhong Chuang; Yusuke Tanaka 002; Tomoharu Iwata (Trans. Mach. Learn. Res., 2025)

Learning Hamiltonian Density Using DeepONet. - Baige Xu; Yusuke Tanaka 002; Takashi Matsubara 001; Takaharu Yaguchi (CoRR, 2025)