Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
We provide a brief guide of the Python QSO fitting code (PyQSOFit) to measure spectral properties of SDSS quasars. The code was originally translated from Yue Shen's IDL code to Python. The package ...
Below is a quick set of instructions to get you started with eryn. Please read CONTRIBUTING for details on our code of conduct, and the process for submitting pull requests to us. See CONTRIBUTORS for ...
Mathematical models of complex systems rely on parameter values to produce a desired behavior. As mathematical and computational models increase in complexity, it becomes correspondingly difficult to ...
Recent advances in computing have accelerated researchers’ ability to amass and analyze data. University of California, Los Angeles mathematical scientist Kenneth Lange uses his expertise in ...
Most patients with congenital heart disease survive into adulthood; however, residual abnormalities remain and management of the patients is life-long and personalized. Patients with surgical repair ...
Purpose: Bayesian calibration is generally superior to standard direct-search algorithms in that it estimates the full joint posterior distribution of the calibrated parameters. However, there are ...
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