Count data are omnipresent in many applied fields, often with overdisper...
This paper addresses the problem of an efficient predictive density
esti...
Most classical SLAM systems rely on the static scene assumption, which l...
Moving objects are present in most scenes of our life. However they can ...
We study frequentist risk properties of predictive density estimators fo...
We propose a new general SLAM system that uses the semantic segmentation...
Tracking humans in crowded video sequences is an important constituent o...
We consider the problem of estimating the mean vector θ of a
d-dimension...
For two vast families of mixture distributions and a given prior, we pro...
Estimating the 3D translation and orientation of an object is a challeng...
The estimation of a multivariate mean θ is considered under natural
modi...
Let X,U,Y be spherically symmetric distributed having density η^d
+k/2 ...
Based on X ∼ N_d(θ, σ^2_X I_d), we study the efficiency of
predictive de...
We describe a hierarchical Bayesian approach for inference about a param...
We present a deep neural network-based method to perform high-precision,...