We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
We present a method for automatically selecting optimal implementations of sparse matrixvector operations. Our software ‘AcCELS’ (Accelerated Compress-storage Elements for Lin...
Alfredo Buttari, Victor Eijkhout, Julien Langou, S...
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
Taking into account input-model, input-parameter, and stochastic uncertainties inherent in many simulations, our Bayesian approach to input modeling yields valid point and confide...
Much of recent action recognition research is based on
space-time interest points extracted from video using a Bag
of Words (BOW) representation. It mainly relies on the discrimi...
Matteo Bregonzio (Queen Mary, University of London...