Search Results for author:
Found 7 papers, 5 papers with code
Recommender Transformers with Behavior Pathways
We conclude this characteristic for sequential behaviors of each user as the Behavior Pathway.
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning
To this end, we propose ModeRNN, which introduces a novel method to learn structured hidden representations between recurrent states.
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions
With high flexibility, this framework can adapt to a series of models for deterministic spatiotemporal prediction.
Towards Good Practices of U-Net for Traffic Forecasting
This technical report presents a solution for the 2020 Traffic4Cast Challenge.
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks
This paper explores a new research problem of unsupervised transfer learning across multiple spatiotemporal prediction tasks.
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains
This paper introduces video domain generalization where most video classification networks degenerate due to the lack of exposure to the target domains of divergent distributions.
Multi-Task Learning of Generalizable Representations for Video Action Recognition
Rev2Net is shown to be effective on the classic action recognition task.
