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Yusuke Tanaka
Yusuke Tanaka
Verified email at hco.ntt.co.jp - Homepage
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Cited by
Year
Deep mixture point processes: Spatio-temporal event prediction with rich contextual information
M Okawa, T Iwata, T Kurashima, Y Tanaka, H Toda, N Ueda
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
482019
Spatially aggregated Gaussian processes with multivariate areal outputs
Y Tanaka, T Tanaka, T Iwata, T Kurashima, M Okawa, Y Akagi, H Toda
Advances in Neural Information Processing Systems 32, 2019
282019
Inferring latent triggers of purchases with consideration of social effects and media advertisements
Y Tanaka, T Kurashima, Y Fujiwara, T Iwata, H Sawada
Proceedings of the ninth ACM international conference on web search and data …, 2016
262016
Estimating latent people flow without tracking individuals.
Y Tanaka, T Iwata, T Kurashima, H Toda, N Ueda
IJCAI, 3556-3563, 2018
232018
Refining coarse-grained spatial data using auxiliary spatial data sets with various granularities
Y Tanaka, T Iwata, T Tanaka, T Kurashima, M Okawa, H Toda
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5091-5099, 2019
162019
Predicting traffic accidents with event recorder data
Y Takimoto, Y Tanaka, T Kurashima, S Yamamoto, M Okawa, H Toda
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction …, 2019
152019
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes
M Okawa, T Iwata, Y Tanaka, H Toda, T Kurashima, H Kashima
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
82021
Exact and efficient inference for collective flow diffusion model via minimum convex cost flow algorithm
Y Akagi, T Nishimura, Y Tanaka, T Kurashima, H Toda
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3163-3170, 2020
72020
Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations
Y Tanaka, T Iwata, T Kurashima, H Toda, N Ueda, T Tanaka
Artificial Intelligence 292, 103430, 2021
62021
Symplectic spectrum Gaussian processes: Learning Hamiltonians from noisy and sparse data
Y Tanaka, T Iwata
Advances in Neural Information Processing Systems 35, 20795-20808, 2022
52022
Few-shot learning for spatial regression via neural embedding-based Gaussian processes
T Iwata, Y Tanaka
Machine Learning, 1-19, 2022
52022
Few-shot learning for spatial regression
T Iwata, Y Tanaka
arXiv preprint arXiv:2010.04360, 2020
52020
Robust naive Bayes combination of multiple classifications
N Ueda, Y Tanaka, A Fujino
The Impact of Applications on Mathematics: Proceedings of the Forum of …, 2014
52014
Context-aware spatio-temporal event prediction via convolutional Hawkes processes
M Okawa, T Iwata, Y Tanaka, T Kurashima, H Toda, H Kashima
Machine Learning 111 (8), 2929-2950, 2022
42022
メタ学習に基づく加速度センサからの看護師行動識別
上田修功, 田中佑典, 中島直樹
マルチメディア, 分散協調とモバイルシンポジウム 2013 論文集 2013, 663-667, 2013
42013
Deep Mixture Point Processes
M Okawa, T Iwata, T Kurashima, Y Tanaka, H Toda, N Ueda, H Kashima
Transactions of the Japanese Society for Artificial Intelligence 36 (5), C-L37, 2021
22021
Probabilistic optimal transport based on collective graphical models
Y Akagi, Y Tanaka, T Iwata, T Kurashima, H Toda
arXiv preprint arXiv:2006.08866, 2020
22020
ドライブレコーダデータに基づくヒヤリハット発生予測
瀧本祥章, 田中佑典, 倉島健, 山本修平, 大川真耶, 戸田浩之
DEIM Forum, 2019
22019
Probabilistic Models for Spatially Aggregated Data
Y Tanaka
Kyoto University, 2020
12020
Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems
M Okawa, Y Tanaka, T Kurashima, H Toda, T Yamada
IEICE TRANSACTIONS on Information and Systems 102 (9), 1635-1643, 2019
12019
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