Search Results for author:
Found 5 papers, 0 papers with code
Spatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking
This integrates future and synthetic past frame memory to enhance the current memory, thereby improving the accuracy of iteration-based tracking.
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
Dynamic Graph Neural Networks (DGNNs) have been broadly applied in various real-life applications, such as link prediction and pandemic forecast, to capture both static structural information and temporal characteristics from dynamic graphs.
Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis
An unsupervised way to construct a social behavior graph based on spatio-temporal data and to model social influences is proposed.
Deep Meta-learning in Recommendation Systems: A Survey
For each recommendation scenario, we further discuss technical details about how existing methods apply meta-learning to improve the generalization ability of recommendation models.
TEMImageNet Training Library and AtomSegNet Deep-Learning Models for High-Precision Atom Segmentation, Localization, Denoising, and Super-Resolution Processing of Atomic-Resolution Images
Atom segmentation and localization, noise reduction and deblurring of atomic-resolution scanning transmission electron microscopy (STEM) images with high precision and robustness is a challenging task.
