Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
We present a new "hp" parameter multi-domain certified reduced basis method for rapid and reliable online evaluation of functional outputs associated with parametrized el...
Jens L. Eftang, Anthony T. Patera, Einar M. R&osla...
We consider the filter decomposition problem in supporting coarse-grained pipelined parallelism. This form of parallelism is suitable for data-driven applications in scenarios wh...
We propose a new approach to the automatic generation of triangular irregular networks from dense terrain models. We have developed and implemented an algorithm based on the greed...
ACT We consider the problem of sensor selection in resource constrained sensor networks. The fusion center selects a subset of k sensors from an available pool of m sensors accordi...
Manohar Shamaiah, Siddhartha Banerjee, Haris Vikal...