Approximate probabilistic analysis of biopathway dynamics

Approximate probabilistic analysis of biopathway dynamics

MOTIVATION Biopathways are often modeled as systems of ordinary differential equations (ODEs). Such systems will usually have many unknown parameters and hence will be difficult to calibrate. Since the data available for calibration will have limited precision, an approximate representation of the ODEs dynamics should suffice. One must, however, be able to efficiently construct such approximati...

Probabilistic complexity analysis for a class of approximate DFT algorithms

We present a probabilistic complexity analysis of a class of multi-stage algorithms which incrementally reene DFT approximations. Each stage of any algorithm in this class improves the results of the previous stage by a xed increment in one of three dimensions: SNR, frequency resolution, or frequency coverage. However, the complexity of each stage is probabilistically dependent upon certain cha...

Approximate Probabilistic Power Flow

Power flow analysis is a necessary tool for operating and planning Power systems. This tool uses a deterministic approach for obtaining the steady state of the system for a specified set of power generation, loads, and network conditions. However this deterministic methodology does not take into account the uncertainty in the power systems, for example variability the in power generation, varia...

Probabilistic Approximate Least-Squares

Least-squares and kernel-ridge / Gaussian process regression are among the foundational algorithms of statistics and machine learning. Famously, the worst-case cost of exact nonparametric regression grows cubically with the data-set size; but a growing number of approximations have been developed that estimate good solutions at lower cost. These algorithms typically return point estimators, wit...

Approximate Probabilistic Confinement