While this library is for now standalone, the goal is to get both the mathematical function as well as the distributions into torch core package. See also pytorch/pytorch#108948. The torchlambertw ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

Department of Computer Science, Metropolitan College, Boston University, Boston, MA, United States On the other hand, using MAD offers a direct measure of deviation and is more resilient to outliers.

Background: Although several strategies for modelling competing events in discrete event simulation (DES) exist, a methodological gap for the event-specific probabilities and distributions (ESPD) ...

Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...

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Abstract: A one-dimensional discrete random variable X describes two populations. A random sample is drawn from each. We formalize a generic statistical test to determine whether the samples provide ...