72 citations · 181 across the 16 of their papers we have counts for
17 papers
Unsupervised and Generic Short-Term Anticipation of Human Body Motions
Kristina Enes, Hassan Errami, Moritz Wolter +4
Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and expla…
Bonn Activity Maps: Dataset Description
Julian Tanke, Oh-Hun Kwon, Patrick Stotko +9
The key prerequisite for accessing the huge potential of current machine learning techniques is the availability of large databases that capture the complex relations of interest.…
Human Motion Anticipation with Symbolic Label
Julian Tanke, Andreas Weber, Juergen Gall
Anticipating human motion depends on two factors: the past motion and the person's intention. While the first factor has been extensively utilized to forecast short sequences of hu…
Efficiently and Effectively Recognizing Toricity of Steady State Varieties
Dima Grigoriev, Alexandru Iosif, Hamid Rahkooy +2
We consider the problem of testing whether the points in a complex or real variety with non-zero coordinates form a multiplicative group or, more generally, a coset of a multiplica…
Identifying the Parametric Occurrence of Multiple Steady States for some Biological Networks
R. Bradford, J. H. Davenport, M. England +8
We consider a problem from biological network analysis of determining regions in a parameter space over which there are multiple steady states for positive real values of variables…
Symbolic Versus Numerical Computation and Visualization of Parameter Regions for Multistationarity of Biological Networks
Matthew England, Hassan Errami, Dima Grigoriev +3
We investigate models of the mitogenactivated protein kinases (MAPK) network, with the aim of determining where in parameter space there exist multiple positive steady states. We b…