Analysis of Different Graph Convolutional Network Prediction Models with Spatial Dependence Evaluation. - Yuting Chen; Jiannan Mao; Hao Huang 004; Qipeng Yan; Weike Lu; Lan Liu 002 (ITSC, 2021)

Mining the Graph Representation of Traffic Speed Data for Graph Convolutional Neural Network. - Jiannan Mao; Hao Huang 004; Yuting Chen; Weike Lu; Guoqiang Chen; Lan Liu 002 (ITSC, 2021)

Multi-precision traffic speed predictions via modified sequence to sequence model and spatial dependency evaluation method. - Jiannan Mao; Hao Huang 004; Weike Lu; Yuting Chen; Lan Liu 002 (Appl. Soft Comput., 2022)

Improving Zero-Shot Dependency Parsing by Unsupervised Learning. - Jiannan Mao; Chenchen Ding; Hour Kaing; Hideki Tanaka; Masao Utiyama; Tadahiro Matsumoto (PACLIC, 2023)

An Enhanced Method for Neural Machine Translation via Data Augmentation Based on the Self-Constructed English-Chinese Corpus, WCC-EC. - Jinyi Zhang; Cong Guo; Jiannan Mao; Chong Guo; Tadahiro Matsumoto (IEEE Access, 2023)

Neural Machine Translation for Low-Resource Languages from a Chinese-centric Perspective: A Survey. - Jinyi Zhang; Ke Su; Haowei Li; Jiannan Mao; Ye Tian 030; Feng Wen; Chong Guo; Tadahiro Matsumoto (ACM Trans. Asian Low Resour. Lang. Inf. Process., 2024)

A dynamic graph deep learning model with multivariate empirical mode decomposition for network-wide metro passenger flow prediction. - Hao Huang 004; Jiannan Mao; Leilei Kang; Weike Lu; Sijia Zhang; Lan Liu 002 (Comput. Aided Civ. Infrastructure Eng., 2024)

MTLMetro: A Deep Multi-Task Learning Model for Metro Passenger Demands Prediction. - Hao Huang 004; Jiannan Mao; Ronghui Liu; Weike Lu; Tianli Tang; Lan Liu 002 (IEEE Trans. Intell. Transp. Syst., 2024)

Origin-Destination Matrix Prediction in Public Transport Networks: Incorporating Heterogeneous Direct and Transfer Trips. - Tianli Tang; Jiannan Mao; Ronghui Liu; Zhiyuan Liu 002; Yiran Wang; Di Huang (IEEE Trans. Intell. Transp. Syst., 2024)

Registering Source Tokens to Target Language Spaces in Multilingual Neural Machine Translation. - Zhi Qu 001; Yiran Wang 006; Jiannan Mao; Chenchen Ding; Hideki Tanaka; Masao Utiyama; Taro Watanabe (ACL (1), 2025)

A convergent cross-mapping approach for unveiling congestion spatial causality in urban traffic networks. - Jiannan Mao; Hao Huang 004; Yu Gu; Weike Lu; Tianli Tang; Fan Ding (Comput. Aided Civ. Infrastructure Eng., 2025)