Sum-product networks (SPNs) have recently emerged as a novel deep learni...
The predictive performance of supervised learning algorithms depends on ...
Professional-grade software applications are powerful but
complicated-ex...
Learning robust value functions given raw observations and rewards is no...
Learning goal-directed behavior in environments with sparse feedback is ...
Traditional topic models do not account for semantic regularities in
lan...
We propose the segmented iHMM (siHMM), a hierarchical infinite hidden Ma...
Models of complex systems are often formalized as sequential software
si...
Markov jump processes (MJPs) are used to model a wide range of phenomena...
In this note we provide detailed derivations of two versions of
small-va...
Approximate inference in high-dimensional, discrete probabilistic models...