This paper presents a system for 3D ultrasound which aims to reconstruct a volume of interest from a set of ultrasound images. A Bayesian reconstruction algorithm has been recently...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Image processing in three-dimensional electron microscopy (3D-EM) is characterized by large amounts of data, and voluminous computing requirements. Here, we report our first exper...
Sjors H. W. Scheres, A. J. Merino, Carlos Oscar S&...
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...