We propose a new technique called node sampling to speed up the probability-based power estimation methods. It samples and processes only a small portion of total nodes to estimat...
Hoon Choi, Hansoo Kim, In-Cheol Park, Seung Ho Hwa...
In this paper we show that rotational invariance can be improved in a neural network based EIT reconstruction approach by a suitably chosen permutation of the input data. The inpu...
Compressed sensing (CS) provides an efficient way to acquire and reconstruct natural images from a reduced number of linear projection measurements at sub-Nyquist sampling rates....
We investigate the use of Antithetic Variables, Control Variates and Importance Sampling to reduce the statistical errors of option sensitivities calculated with the Likelihood Ra...
In this research, we investigate how well Weibull, Gamma, and special bimodal distribution are suited as an alternative to the exponential distribution approach in the stochastic ...