Follow
Takashi Nicholas MAEDA
Takashi Nicholas MAEDA
Verified email at mail.dendai.ac.jp - Homepage
Title
Cited by
Cited by
Year
Extraction of tourist destinations and comparative analysis of preferences between foreign tourists and domestic tourists on the basis of geotagged social media data
TN Maeda, M Yoshida, F Toriumi, H Ohashi
ISPRS International Journal of Geo-Information 7 (3), 99, 2018
472018
RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders
TN Maeda, S Shimizu
International Conference on Artificial Intelligence and Statistics, 735-745, 2020
292020
Decision tree analysis of tourists' preferences regarding tourist attractions using geotag data from social media
TN Maeda, M Yoshida, F Toriumi, H Ohashi
Proceedings of the Second International Conference on IoT in Urban Space, 61-64, 2016
212016
Detecting and understanding urban changes through decomposing the numbers of visitors’ arrivals using human mobility data
TN Maeda, N Shiode, C Zhong, J Mori, T Sakimoto
Journal of Big Data 6, 1-25, 2019
192019
Comparative examination of network clustering methods for extracting community structures of a city from public transportation smart card data
TN Maeda, J Mori, I Hayashi, T Sakimoto, I Sakata
IEEE Access 7, 53377-53391, 2019
132019
Causal additive models with unobserved variables
TN Maeda, S Shimizu
Uncertainty in Artificial Intelligence, 97-106, 2021
112021
Next place prediction in unfamiliar places considering contextual factors
TN Maeda, K Tsubouch, F Toriumi
The 25th ACM SIGSPATIAL International Conference on Advances in Geographic …, 2017
102017
Python package for causal discovery based on LiNGAM
T Ikeuchi, M Ide, Y Zeng, TN Maeda, S Shimizu
Journal of Machine Learning Research 24 (14), 1-8, 2023
82023
前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦: EBPM と統計的因果探索・数理モデルの利活用
高山正行, 小柴
研究・イノベーション学会 第 36 回年次学術大会 (予稿集)., 公演番号 2G02, 2021
52021
Repetitive causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders
TN Maeda, S Shimizu
International Journal of Data Science and Analytics, 1-13, 2022
42022
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
M Suzuki, J Mori, TN Maeda, J Ikeda
Journal of Asian Architecture and Building Engineering 22 (3), 1110-1125, 2023
32023
前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦: 博士課程進学率に関する因果モデルの構築: 統計的因果探索アルゴリズム “LiNGAM” による試行的分析
高山正行, 小柴
Jxiv preprint, 2022
32022
Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders
TN Maeda, S Shimizu
arXiv preprint arXiv:2001.04197, 2020
32020
Measurement of Opportunity Cost of Travel Time for Predicting Future Residential Mobility Based on the Smart Card Data of Public Transportation
TN Maeda, J Mori, M Ochi, T Sakimoto, I Sakata
ISPRS international journal of geo-information 7 (11), 416, 2018
32018
Analysis of smart card data for understanding spatial changes in consumption-oriented human flows
TN Maeda, J Mori, F Toriumi, H Ohashi
Proceedings of the 2nd ACM SIGSPATIAL Workshop on Smart Cities and Urban …, 2016
32016
統計的因果探索アルゴリズム “LiNGAM” を用いた若手研究者支援政策に関する研究
高山正行, 小柴, 前田高志, 三内顕義, 清水昌平, 星野利彦
研究・イノベーション学会, 2021
22021
Discovery of causal additive models in the presence of unobserved variables
TN Maeda, S Shimizu
arXiv preprint arXiv:2106.02234, 2021
22021
I-RCD: an improved algorithm of repetitive causal discovery from data with latent confounders
TN Maeda
Behaviormetrika 49 (2), 329-341, 2022
12022
EBPM と統計的因果探索・数理モデルの利活用
高山正行, 小柴, 前田高志, 三内顕義, 清水昌平, 星野利彦
研究・イノベーション学会, 2021
12021
Use of Prior Knowledge to Discover Causal Additive Models with Unobserved Variables and its Application to Time Series Data
TN Maeda, S Shohei
arXiv preprint arXiv:2401.07231, 2024
2024
The system can't perform the operation now. Try again later.
Articles 1–20