Protein structure determination and prediction has been a focal research subject in life sciences due to the importance of protein structure in understanding the biological and ch...
The complexity of quantitative biomedical models, and the rate at which they are published, is increasing to a point where managing the information has become all but impossible w...
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
This paper introduces a novel method for real-time estimation of slowly varying parameters in nonlinear dynamical systems. The core concept is built upon the principles of symboli...