Liu, Juncheng

11 publications

ICML 2025 Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Junnan Li, Silvio Savarese, Caiming Xiong, Doyen Sahoo

TMLR 2025 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

NeurIPSW 2024 GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation Taha Aksu, Gerald Woo, Juncheng Liu, Xu Liu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

NeurIPSW 2024 Mixture of Experts for Time Series Foundation Models Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

ICLR 2024 Scalable and Effective Implicit Graph Neural Networks on Large Graphs Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao

NeurIPSW 2024 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

AAAI 2022 A Fusion-Denoising Attack on InstaHide with Data Augmentation Xinjian Luo, Xiaokui Xiao, Yuncheng Wu, Juncheng Liu, Beng Chin Ooi

ECML-PKDD 2022 LSCALE: Latent Space Clustering-Based Active Learning for Node Classification Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao

NeurIPS 2022 MGNNI: Multiscale Graph Neural Networks with Implicit Layers Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

NeurIPS 2021 EIGNN: Efficient Infinite-Depth Graph Neural Networks Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao

CVPR 2017 Incremental Kernel Null Space Discriminant Analysis for Novelty Detection Juncheng Liu, Zhouhui Lian, Yi Wang, Jianguo Xiao