Sparsity of target space in subsurface imaging problem is used within the framework of the compressive sensing (CS) theory in recent publications to decrease the data acquisition ...
We analyze the problem of reconstructing a 2D function that approximates a set of desired gradients and a data term. The combined data and gradient terms enable operations like mod...
Pravin Bhat, Brian Curless, Michael F. Cohen, C. L...
In this paper we present a methodology and techniques for generating cycle-accurate macro-models for RTlevel power analysis. The proposed macro-model predicts not only...
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Background: Protein conformation and protein/protein interaction can be elucidated by solution-phase Hydrogen/ Deuterium exchange (sHDX) coupled to high-resolution mass analysis o...
Ernst Althaus, Stefan Canzar, Carsten Ehrler, Mark...