Statistical Learning
EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection
This study proposes a novel framework, Event-based Graph Spatiotemporal Sensitive Transformer (EGSST), for the exploitation of spatial and temporal properties of event data.
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes Y unyue Wei 1, Vincent Zhuang
Using sparse GP models is a popular method for reducing the computational cost of BO.
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems Kurt Butler
The TSCI approach is model-agnostic and can be used as a drop-in replacement for CCM and its generalizations.
ConjugateBayesianTwo-stepChangePointDetection forHawkesProcess
Additionally, we conduct ablation studies to explore the robustness of our method concerning various hyperparameters.
Most Influential Subset Selection: Challenges, Promises, and Beyond Y uzheng Hu
Subset Selection (MISS) problem, which aims to identify a subset of training samples with the greatest collective influence.
