This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Public biological databases contain vast amounts of rich data that can also be used to create and evaluate new biological hypothesis. We propose a method for link discovery in biol...
Petteri Sevon, Lauri Eronen, Petteri Hintsanen, Ki...
Abstract—Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in vehicles. In this contribution the probability hypothesis density (PHD) ...
Christian Lundquist, Lars Hammarstrand, Fredrik Gu...
In this paper we describe a method to learn parameters
which govern pedestrian motion by observing video
data. Our learning framework is based on variational
mode learning and a...
This paper presents a framework called Parallel Experiment Planning (PEP) that is based on an abstraction of how experiments are performed in the domain of macromolecular crystall...
Vanathi Gopalakrishnan, Bruce G. Buchanan, John M....