The TensorFlow Distributions library implements a vision of probability theory adapted to the modern deep-learning paradigm of end-to-end differentiable computation. Building on two basic abstractions, it offers flexible building blocks for probabili...
We introduce a new five-parameter family of size distributions on the semi-finite interval $[x_0, \infty), x_0 \geqslant 0$, with two attractive features. First, it interpolates between power laws, such as the Pareto distribution, and power laws with...
We calculate the double differential distributions and distributions in recoil momenta for the high energy non-relativistic double photoionization of helium. We show that the results of recent experiments is the pioneering experimental manifestation...
The theory of Barnes beta probability distributions is advanced and related to the Riemann xi function. The scaling invariance, multiplication formula, and Shintani factorization of Barnes multiple gamma functions are reviewed using the approach of R...
Current variational dialog models have employed pre-trained language models (PLMs) to parameterize the likelihood and posterior distributions. However, the Gaussian assumption made on the prior distribution is incompatible with these distributions, t...
Nous avons analyse les distributions angulaires de la diffusion elastique pour differents systemes a des energies proches de la barriere de Coulomb au moyen d'un potentiel semi phenomenologique. Les distributions radiales calculees au moyen de ces...
Normalizing Flows are a powerful technique for learning and modeling probability distributions given samples from those distributions. The current state of the art results are built upon residual flows as these can model a larger hypothesis space tha...
We study the multiplicity distributions of events with hard jets in proton-proton collisions at LHC energies using PYTHIA 8 Monte-Carlo simulations. We demonstrate that the charged-hadron multiplicity distributions scale with jet momentum. This sugge...
We characterise modulation spaces by suitable Wiener estimates on the short-time Fourier transforms of the involved functions and distributions. We use the results to refine some formulae on periodic distributions with Lebesgue estimates on their coe...
We show that the lensing efficiency of cosmic shear generically has a simple shape, even in the case of a tomographic survey with badly behaved photometric redshifts. We argue that source distributions for cosmic shear can therefore be more effective...
theory, suggests that more egalitarian distributions of wealth are more efficient than inegalitarian distributions. Distributive inefficiency is often associated
Wikimedia Commons has media related to Discrete distributions.
Wikimedia Commons has media related to Functions related to probability distributions.
Wikimedia Commons has media related to Tails of probability distributions.
Stable distributions are of fundamental importance in probability theory, yet their absolute continuity makes them unsuitable for modeling count data. A discrete analog of strict stability has been previously proposed by replacing scaling with binomi...
Mixed Poisson distributions provide a flexible approach to the analysis of count data with overdispersion, zero inflation, or heavy tails. Since the Poisson mean must be nonnegative, the mixing distribution is typically assumed to have nonnegative su...
May 1, 2017 · Links to popular distribution download pages 24 Popular Linux Distributions Explore different Linux distributions and find the one that fits your needs. Try distrowatch.com for more options.
We extend our analysis of quasi-distributions onto the pion distribution amplitude. Using the formalism of parton virtuality distribution amplitudes (VDAs), we establish a connection between the pion transverse momentum dependent distribution amplitu...
We examine whether the principle of detailed balance holds for the power-law distributions generated from the general Langevin equation under the generalized fluctuation-dissipation relation (FDR). With the detailed balance and the generalized FDR, w...
As alternatives to the normal distributions, $t$ distributions are widely applied in robust analysis for data with outliers or heavy tails. The properties of the multivariate $t$ distribution are well documented in Kotz and Nadarajah's book, which, h...