Convergence of random variablesIn probability theory, there exist several different notions of convergence of random variables. The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and its applications to statistics and stochastic processes. The same concepts are known in more general mathematics as stochastic convergence and they formalize the idea that a sequence of essentially random or unpredictable events can sometimes be expected to settle down into a behavior that is essentially unchanging when items far enough into the sequence are studied.
Logistic distributionIn probability theory and statistics, the logistic distribution is a continuous probability distribution. Its cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks. It resembles the normal distribution in shape but has heavier tails (higher kurtosis). The logistic distribution is a special case of the Tukey lambda distribution.
Alternating finite automatonIn automata theory, an alternating finite automaton (AFA) is a nondeterministic finite automaton whose transitions are divided into existential and universal transitions. For example, let A be an alternating automaton. For an existential transition , A nondeterministically chooses to switch the state to either or , reading a. Thus, behaving like a regular nondeterministic finite automaton. For a universal transition , A moves to and , reading a, simulating the behavior of a parallel machine.
Unit disk graphIn geometric graph theory, a unit disk graph is the intersection graph of a family of unit disks in the Euclidean plane. That is, it is a graph with one vertex for each disk in the family, and with an edge between two vertices whenever the corresponding vertices lie within a unit distance of each other. They are commonly formed from a Poisson point process, making them a simple example of a random structure.
Uniform spaceIn the mathematical field of topology, a uniform space is a topological space with additional structure that is used to define uniform properties, such as completeness, uniform continuity and uniform convergence. Uniform spaces generalize metric spaces and topological groups, but the concept is designed to formulate the weakest axioms needed for most proofs in analysis. In addition to the usual properties of a topological structure, in a uniform space one formalizes the notions of relative closeness and closeness of points.
Bounded expansionIn graph theory, a family of graphs is said to have bounded expansion if all of its shallow minors are sparse graphs. Many natural families of sparse graphs have bounded expansion. A closely related but stronger property, polynomial expansion, is equivalent to the existence of separator theorems for these families. Families with these properties have efficient algorithms for problems including the subgraph isomorphism problem and model checking for the first order theory of graphs.
Uniform isomorphismIn the mathematical field of topology a uniform isomorphism or is a special isomorphism between uniform spaces that respects uniform properties. Uniform spaces with uniform maps form a . An isomorphism between uniform spaces is called a uniform isomorphism. A function between two uniform spaces and is called a uniform isomorphism if it satisfies the following properties is a bijection is uniformly continuous the inverse function is uniformly continuous In other words, a uniform isomorphism is a uniformly continuous bijection between uniform spaces whose inverse is also uniformly continuous.
Permian–Triassic extinction eventThe Permian–Triassic (P–T, P–Tr) extinction event (PTME), also known as the Late Permian extinction event, the Latest Permian extinction event, the End-Permian extinction event, and colloquially as the Great Dying, forms the boundary between the Permian and Triassic geologic periods, and with them the Paleozoic and Mesozoic eras respectively, approximately 251.9 million years ago. As the largest of the "Big Five" mass extinctions of the Phanerozoic, it is the Earth's most severe known extinction event, with the extinction of 57% of biological families, 83% of genera, 81% of marine species and 70% of terrestrial vertebrate species.
Human extinctionHuman extinction is the hypothetical end of the human species due to either natural causes such as population decline from sub-replacement fertility, an asteroid impact, large-scale volcanism, or via anthropogenic destruction (self-extinction). For the latter, some of the many possible contributors include climate change, global nuclear annihilation, biological warfare, and ecological collapse. Other scenarios center on emerging technologies, such as advanced artificial intelligence, biotechnology, or self-replicating nanobots.
Tweedie distributionIn probability and statistics, the Tweedie distributions are a family of probability distributions which include the purely continuous normal, gamma and inverse Gaussian distributions, the purely discrete scaled Poisson distribution, and the class of compound Poisson–gamma distributions which have positive mass at zero, but are otherwise continuous. Tweedie distributions are a special case of exponential dispersion models and are often used as distributions for generalized linear models.