Ratios of normalizing constants for two distributions are needed in both Bayesian statistics, where they are used to compare models, and in statistical physics, where they correspond to differences in free energy. Two approaches have long been used...
Bi$_2$Se$_3$ is a topological insulator and it is often doped with Te to compensate the $n$-type carriers due to Se vacancies. Different doping patterns of Te would influence the transport characteristics of the surface states. We study the Te atom d...
Dataset distillation synthesizes a small set of images from a large-scale real dataset such that synthetic and real images share similar behavioral properties (e.g, distributions of gradients or features) during a training process. Through extensive...
It is shown that in the instanton approximation the rate of creation of black holes is always enhanced by a factor of the exponential of the black hole entropy relative to the rate of creation of compact matter distributions (stars). This result ho...
We calculate crossing probabilities and one-sided last exit time densities for a class of moving barriers on an interval $[0,T]$ via Schwartz distributions. We derive crossing probabilities and first hitting time densities for another class of barr...
Feb 14, 2026 · Probability is a subject that deals with uncertainty. In everyday terminology, probability can be thought of as a numerical measure of the likelihood that a particular event will occur.
The Multi-Armed Bandit (MAB) problem is challenging in non-stationary environments where reward distributions evolve dynamically. We introduce RAVEN-UCB, a novel algorithm that combines theoretical rigor with practical efficiency via variance-aware a...
treatment similar to a 401(k) plan, especially after the Economic Growth and Tax Relief Reconciliation Act of 2001. Both plans also require that distributions
The declination is a quantitative method for identifying possible partisan gerrymanders by analyzing vote distributions. In this expository note we explain and motivate the definition of the declination. The minimal computer code required for computi...
Probabilistic forecasting in power systems often involves multi-entity datasets like households, feeders, and wind turbines, where generating reliable entity-specific forecasts presents significant challenges. Traditional approaches require training...
the normal-Wishart distribution (or Gaussian-Wishart distribution) is a multivariate four-parameter family of continuous probability distributions. It
specified in the theorem. A characterization of a probability distribution accordingly states that it is the only probability distribution that satisfies specified
generalized normal distribution (GND) or generalized Gaussian distribution (GGD) is either of two parametric families of continuous probability distributions on
use statsmodels.distributions.empirical_distribution.ECDF Matplotlib, using the matplotlib.pyplot.ecdf function (new in version 3.8.0) Seaborn, using
The paper describes the different methods, used in the MAGIC experiment, to unfold experimental energy distributions of cosmic ray particles (gamma-rays). Questions and problems related to the unfolding are discussed. Various procedures are propose...
This paper is a continuation of the systematic study of the distributions of quadrant marked mesh patterns initiated in [6]. Given a permutation $\sg = \sg_1 ... \sg_n$ in the symmetric group $S_n$, we say that $\sg_i$ matches the quadrant marked mes...
We introduce an extension of the Pólya tree approach for constructing distributions on the space of probability measures. By using optional stopping and optional choice of splitting variables, the construction gives rise to random measures that are...
Tree shape statistics are important for investigating evolutionary mechanisms mediating phylogenetic trees. As a step towards bridging shape statistics between rooted and unrooted trees, we present a comparison study on two subtree statistics known a...
An overview of theoretical and experimental progress in double parton scattering (DPS) is presented. The theoretical topics cover factorization in DPS, models for double parton distributions and DPS in charm production and nuclear collisions. On the...
We introduce a new approach for amortizing inference in directed graphical models by learning heuristic approximations to stochastic inverses, designed specifically for use as proposal distributions in sequential Monte Carlo methods. We describe a pr...