Search Results for author:
Found 5 papers, 3 papers with code
Reduced-Order Autodifferentiable Ensemble Kalman Filters
This paper introduces a computational framework to reconstruct and forecast a partially observed state that evolves according to an unknown or expensive-to-simulate dynamical system.
Towards Spatial Equilibrium Object Detection
In this paper, we study the spatial disequilibrium problem of modern object detectors and propose to quantify this ``spatial bias'' by measuring the detection performance over zones.
Extracting and Measuring Uncertain Biomedical Knowledge from Scientific Statements
Design/methodology/approach: Taking cardiovascular research publications in China as a sample, we extracted the SPO triples as knowledge unit and the hedging/conflicting uncertainties as the knowledge context.
Auto-differentiable Ensemble Kalman Filters
Data assimilation is concerned with sequentially estimating a temporally-evolving state.
Place recognition: An Overview of Vision Perspective
Place recognition is one of the most fundamental topics in computer vision and robotics communities, where the task is to accurately and efficiently recognize the location of a given query image.
