Pulsar Bayesian Model: A Comprehensive Astronomical Data Fitting Model - Yu, Hang; Yin, Qian; Guo, Ping (Neural Information Processing, 2017)
Pulsar, as a hotspot in the field of astronomy, has a great help of electronic communications, cosmic media detection, and timing. Scientists expect to know the distributions that the data of pulsar features is most likely to be subject to. There are off-the-shelf approaches for scientific researchers to do that, while they are either not fully-using statistical properties or computing-resource-wasting. As an accurate and convenient solution to the problem, we propose a comprehensive fitting model with Bayesian prior knowledge to help scientists automatically fit pulsar data into the optimal expression.