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Found 4 papers, 1 papers with code
Flexible Multi-Generator Model with Fused Spatiotemporal Graph for Trajectory Prediction
Trajectory prediction plays a vital role in automotive radar systems, facilitating precise tracking and decision-making in autonomous driving.
Model-based Transfer Learning for Automatic Optical Inspection based on domain discrepancy
However, related research enhanced the network models by applying TL without considering the domain similarity among datasets, the data long-tailedness of a source dataset, and mainly used linear transformations to mitigate the lack of samples.
Context-aware Heterogeneous Graph Attention Network for User Behavior Prediction in Local Consumer Service Platform
Hence, in this paper, we propose a context-aware heterogeneous graph attention network (CHGAT) to dynamically generate the representation of the user and to estimate the probability for future behavior.
Slice Sampling for General Completely Random Measures
Completely random measures provide a principled approach to creating flexible unsupervised models, where the number of latent features is infinite and the number of features that influence the data grows with the size of the data set.
