Juntao Fang — accepted AI-conference papers

2026

Disentangling Coarse and Fine Latent Dynamics for Probabilistic Time Series Forecasting

Changze Zhou, Ruichu Cai, Shengbin Nie, Juntao Fang, Jie Qiao, Zijian Li

IJCAI 2026

Probabilistic time series forecasting seeks to quantify the uncertainty of future observations. While recent works introduce latent variables to alleviate the spurious dependencies caused by hidden confounders, thereby reducing overly wide confidence intervals, simply incorporating latent factors is

Cited by 0 Scholar ↗

2026

Hierarchical Action Learning for Weakly-Supervised Action Segmentation

Junxian Huang, Ruichu Cai, Juntao Fang, Hao Zhu, Boyan Xu, Weilin Chen +2

CVPR 2026

Humans perceive actions through key transitions that structure actions across multiple abstraction levels, whereas machines, relying on visual features, tend to over-segment. This highlights the difficulty of enabling hierarchical reasoning in video understanding. Interestingly, we observe that lowe

Cited by 0 Source ↗code ↗Scholar ↗