the category of Markov kernels, often denoted Stoch, is the category whose objects are measurable spaces and whose morphisms are Markov kernels. It is...

of a category on the measurable spaces with Markov kernels as morphisms, first defined by Lawvere, the category of Markov kernels. A composition of a...

Measurable space Markov kernel Monad (category theory) Monad (functional programming) Category of measurable spaces Category of Markov kernels Categorical...

structures in the theory are The category of measurable spaces; Markov categories such as the category of Markov kernels; Probability monads such as Giry...

backward equation Examples of Markov chains Category of Markov kernels Perrone (2024), pp. 10–11 Pavliotis, Grigorios A. (2014). "Markov Processes and the Chapman–Kolmogorov...

functions Category of measure spaces Category of Markov kernels – Category whose objects are measurable spaces and whose morphisms are Markov kernels Measurable...

sequence of length 3, let alone an infinitely long one. De Finetti's theorem can be expressed as a categorical limit in the category of Markov kernels. Let...

stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number representing a probability...

Given a classification of a specific data set, there are four basic combinations of actual data category and assigned category: true positives TP (correct...

nonparametric methods like kernel density estimation (Note: the smoothing kernels in this context have a different interpretation than the kernels discussed here)...

and applications. Developing kernel PCA, Schölkopf extended it to extract invariant features and to design invariant kernels and showed how to view other...

Completeness (statistics) Non-parametric statistics Nonparametric regression Kernels Kernel method Statistical learning theory Rademacher complexity Vapnik–Chervonenkis...

LogitBoost Manifold alignment Markov chain Monte Carlo (MCMC) Minimum redundancy feature selection Mixture of experts Multiple kernel learning Non-negative matrix...

Artificial neural networks Game theory Bayesian probability Consciousness Markov kernels Signal-flow graphs Conjunctive queries Bidirectional transformations...

process Markov information source Markov kernel Markov logic network Markov model Markov network Markov process Markov property Markov random field Markov renewal...

algorithms is that the latter do not assume knowledge of an exact mathematical model of the Markov decision process, and they target large MDPs where exact...

networks and Markov random fields. Both families encompass the properties of factorization and independences, but they differ in the set of independences...

condition is then an expression of the Markov property of Brownian motion. In higher-dimensional Euclidean space Rn, the heat kernel is η ε = 1 ( 2 π ε ) n /...

independent Markov machine. Each time a particular arm is played, the state of that machine advances to a new one, chosen according to the Markov state evolution...

corresponding kernel dimension. For example, a convolutional layer using 3x3 kernels would receive a 2-pixel pad, that is 1 pixel on each side of the image...

A Markov-modulated denial-of-service attack occurs when the attacker disrupts control packets using a hidden Markov model. A setting in which Markov-model...

uniqueness conjecture for Markov numbers that every Markov number is the largest number in exactly one normalized solution to the Markov Diophantine equation...

customer service, social media, and marketing. Hopfield network Markov random field Markov chain Monte Carlo Hendriksen, Mariya; Bleeker, Maurits; Vakulenko...

the compression of data; it employs the Lempel–Ziv–Markov chain algorithm (LZMA) with a user interface that is familiar to users of usual Unix compression...

procedures tend to be computationally expensive and, in the days before Markov chain Monte Carlo computations were developed, approximations for Bayesian...

R.; Schmidt, K. (1972). Positive Definite Kernels, Continuous Tensor Products, and Central Limit Theorems of Probability Theory. Springer. ISBN 978-3-540-37607-1...

Andrey Markov Jr. described two moves on braid diagrams that yield equivalence in the corresponding closed braids. A single-move version of Markov's theorem...

designed to measure abstract reasoning, and found it scored below 33% on all categories, while models specialized for similar tasks scored 60% on most, and humans...

Markov additive process Markov blanket / Bay Markov chain mixing time / (L:D) Markov decision process Markov information source Markov kernel Markov logic...

International Journal of Computer Vision. 123: 32–73. arXiv:1602.07332. doi:10.1007/s11263-016-0981-7. S2CID 4492210. Karayev, S., et al. "A category-level 3-D object...