Accurate noise level estimation is essential to assure good performance of noise reduction filters. Noise contaminating raw images is typically modeled as additive white and Gauss...
Angelo Bosco, Arcangelo Bruna, D. Giacalone, Sebas...
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
John P. Cunningham, Krishna V. Shenoy, Maneesh Sah...
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
— In this paper, we study the asymptotic behavior of the bit–error probability (BEP) and symbol–error probability (SEP) of differential M–ary phase–shift keying with diff...