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Large language and music models are increasingly used for constrained generation: rhyming lines, fixed meter, inpainting or infilling, positional endings, and other global form requirements. These systems often perform strikingly well, but…

Artificial Intelligence · Computer Science 2026-04-10 Francois Pachet , Pierre Roy

We may attempt to encapsulate what we know about a physical system by a model structure, $S$. This collection of related models is defined by parametric relationships between system features; say observables (outputs), unobservable…

Methodology · Statistics 2021-02-16 Jason M. Whyte

Conditional independence plays a foundational role in database theory, probability theory, information theory, and graphical models. In databases, conditional independence appears in database normalization and is known as the (embedded)…

Databases · Computer Science 2023-12-19 Miika Hannula

Symmetric informationally complete measurements (SICs) are elegant, celebrated and broadly useful discrete structures in Hilbert space. We introduce a more sophisticated discrete structure compounded by several SICs. A SIC-compound is…

Quantum Physics · Physics 2020-10-26 Armin Tavakoli , Ingemar Bengtsson , Nicolas Gisin , Joseph M. Renes

Given a graph $G$, we study the number of independent sets in $G$, denoted $i(G)$. This parameter is known as both the Merrifield-Simmons index of a graph as well as the Fibonacci number of a graph. In this paper, we give general bounds for…

Combinatorics · Mathematics 2023-11-28 Michael Han , Sycamore Herlihy , Kirsti Kuenzel , Daniel Martin , Rachel Schmidt

The paper introduces a generalization for known probabilistic models such as log-linear and graphical models, called here multiplicative models. These models, that express probabilities via product of parameters are shown to capture…

Artificial Intelligence · Computer Science 2012-06-18 Ydo Wexler , Christopher Meek

A minimal homogeneous generating system of the algebra of semi-invariants of tuples of two-by-two matrices over an infinite field of characteristic two or over the ring of integers is given. In an alternative interpretation this yields a…

Commutative Algebra · Mathematics 2020-01-01 M. Domokos

Recent years have witnessed the impressive progress in Neural Dependency Parsing. According to the different factorization approaches to the graph joint probabilities, existing parsers can be roughly divided into autoregressive and…

Computation and Language · Computer Science 2023-06-22 Ye Ma , Mingming Sun , Ping Li

Probabilistic independence can dramatically simplify the task of eliciting, representing, and computing with probabilities in large domains. A key technique in achieving these benefits is the idea of graphical modeling. We survey existing…

Artificial Intelligence · Computer Science 2013-02-21 Fahiem Bacchus , Adam J. Grove

In this present work, we discuss the Bayesian inference for the bivariate pseudo-exponential distribution. Initially, we assume independent gamma priors and then pseudo-gamma priors for the pseudo-exponential parameters. We are primarily…

Methodology · Statistics 2023-06-27 Banoth Veeranna

Comparability graphs are a popular class of graphs. We introduce as the digraph analogue of comparability graphs the class of comparability digraphs. We show that many concepts such as implication classes and the knotting graph for a…

Combinatorics · Mathematics 2022-04-05 Xiao-Lu Gao , Jing Huang , Shou-Jun Xu

We develop an effective and natural approach to interpret any semigroup admitting a special language of greedy normal forms as an automaton semigroup,namely the semigroup generated by a Mealy automaton encoding the behaviour of such a…

Group Theory · Mathematics 2018-12-06 Matthieu Picantin

Gaussian graphical models typically assume a homogeneous structure across all subjects, which is often restrictive in applications. In this article, we propose a weighted pseudo-likelihood approach for graphical modeling which allows…

Methodology · Statistics 2023-03-17 Sutanoy Dasgupta , Peng Zhao , Jacob Helwig , Prasenjit Ghosh , Debdeep Pati , Bani K. Mallick

Identification theory for causal effects in causal models associated with hidden variable directed acyclic graphs (DAGs) is well studied. However, the corresponding algorithms are underused due to the complexity of estimating the…

Machine Learning · Statistics 2022-10-17 Rohit Bhattacharya , Razieh Nabi , Ilya Shpitser

The finite sample properties of estimators are usually understood or approximated using asymptotic theories. Two main asymptotic constructions have been used to characterize the presence of many instruments. The first assumes that the…

Econometrics · Economics 2021-06-30 Guy Tchuente

Stacking probabilistic building blocks into deeper architectures typically breaks closed-form inference. We show that closed-form inference can be preserved. We identify five factor-graph primitives: a bilinear factor, an exponential link,…

Machine Learning · Computer Science 2026-05-29 Mykola Lukashchuk , Kyrylo Yemets , Wouter M. Kouw , Dmitry Bagaev , İsmail Şenöz , Jeff Beck , Bert de Vries

We apply, in the context of semigroups, the main theorem from~\cite{higjac} that an elementary class $\mathcal{C}$ of algebras which is closed under the taking of direct products and homomorphic images is defined by systems of equations. We…

Logic · Mathematics 2023-08-25 Peter M. Higgins , Marcel Jackson

For any semiring, the concept of k-congruences is introduced, criteria for k-congruences are established, it is proved that there is an inclusion-preserving bijection between k-congruences and k-ideals, and an equivalent condition for the…

Rings and Algebras · Mathematics 2016-10-04 Song-Chol Han

We prove two characterisations of accessibility of locally finite quasi-transitive connected graphs. First, we prove that any such graph $G$ is accessible if and only if its set of separations of finite order is an ${\rm Aut}(G)$-finitely…

Combinatorics · Mathematics 2024-09-05 Matthias Hamann , Babak Miraftab

We present a theory for slicing probabilistic imperative programs -- containing random assignments, and ``observe'' statements (for conditioning) -- represented as probabilistic control-flow graphs (pCFGs) whose nodes modify probability…

Programming Languages · Computer Science 2017-11-08 Torben Amtoft , Anindya Banerjee