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Semantic composition remains an open problem for vector space models of semantics. In this paper, we explain how the probabilistic graphical model used in the framework of Functional Distributional Semantics can be interpreted as a…

Computation and Language · Computer Science 2017-09-04 Guy Emerson , Ann Copestake

We investigate some types of composition operators, linear and not, and conditions for some spaces to be mapped into themselves and for the operators to satisfy some good properties.

Functional Analysis · Mathematics 2020-12-08 Emma D'Aniello , Martina Maiuriello

Probabilistic sentential decision diagrams are logic circuits where the inputs of disjunctive gates are annotated by probability values. They allow for a compact representation of joint probability mass functions defined over sets of…

Artificial Intelligence · Computer Science 2020-08-20 Lilith Mattei , Alessandro Antonucci , Denis Deratani Mauá , Alessandro Facchini , Julissa Villanueva Llerena

In this paper, an algorithm for construction of multiple sets of two dimensional (2D) or matrix unipolar (optical) orthogonal codes has been proposed. Representations of these 2D codes in difference of positions representation (DoPR) have…

Information Theory · Computer Science 2013-09-10 Ram Chandra Singh Chauhan , Yatindra Nath Singh , Rachna Asthana

In this paper, we study weighted composition operators on Bergman spaces of analytic functions which are square integrable on polydisk. We develop the study in full generality, meaning that the corresponding weighted composition operators…

Complex Variables · Mathematics 2022-09-13 Pham Viet Hai

This work is an analytical and numerical study of the composition of several fractals into one and of the relation between the composite dimension and the dimensions of the component fractals. In the case of composition of standard IFS with…

Metric Geometry · Mathematics 2020-10-20 Yann Lanoiselee , Laurent Nivanen , Aziz El Kaabouchi , Qiuping A. Wang

Many machine learning algorithms represent input data with vector embeddings or discrete codes. When inputs exhibit compositional structure (e.g. objects built from parts or procedures from subroutines), it is natural to ask whether this…

Machine Learning · Computer Science 2019-04-09 Jacob Andreas

Probabilistic circuits (PCs) are a class of tractable probabilistic models, which admit efficient inference routines depending on their structural properties. In this paper, we introduce md-vtrees, a novel structural formulation of…

Artificial Intelligence · Computer Science 2023-04-18 Benjie Wang , Marta Kwiatkowska

In this work we study the framework of mathematical morphology on simplicial complex spaces. Simplicial complexes are widely used to represent multidimensional data, such as meshes, that are two dimensional complexes, or graphs, that can be…

Discrete Mathematics · Computer Science 2014-01-23 Fabio Dias , Jean Cousty , Laurent Najman

For quadratic spaces which represent 1 there is a characterization of hermitian compositions in the language of algebras-with-involutions using the even Clifford algebra. We extend this notion to define a generalized composition based on…

Commutative Algebra · Mathematics 2008-09-25 Roland Lötscher

Bisimulation metric is a robust behavioural semantics for probabilistic processes. Given any SOS specification of probabilistic processes, we provide a method to compute for each operator of the language its respective metric…

Programming Languages · Computer Science 2014-08-08 Daniel Gebler , Simone Tini

Predictions in the form of sets of probability distributions, so-called credal sets, provide a suitable means to represent a learner's epistemic uncertainty. In this paper, we propose a theoretically grounded approach to credal prediction…

Machine Learning · Statistics 2025-12-16 Timo Löhr , Paul Hofman , Felix Mohr , Eyke Hüllermeier

A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations…

Machine Learning · Computer Science 2021-05-20 Jacob Russin , Roland Fernandez , Hamid Palangi , Eric Rosen , Nebojsa Jojic , Paul Smolensky , Jianfeng Gao

We introduce an orbifold induction procedure which provides a systematic construction of cyclic orbifolds, including their twisted sectors. The procedure gives counterparts in the orbifold theory of all the current-algebraic constructions…

High Energy Physics - Theory · Physics 2014-11-18 L. Borisov , M. B. Halpern , C. Schweigert

We investigate compositional structures in data embeddings from pre-trained vision-language models (VLMs). Traditionally, compositionality has been associated with algebraic operations on embeddings of words from a pre-existing vocabulary.…

Machine Learning · Computer Science 2024-01-12 Matthew Trager , Pramuditha Perera , Luca Zancato , Alessandro Achille , Parminder Bhatia , Stefano Soatto

Probabilistic circuits (PCs) represent a probability distribution as a computational graph. Enforcing structural properties on these graphs guarantees that several inference scenarios become tractable. Among these properties, structured…

Machine Learning · Computer Science 2020-09-03 Meihua Dang , Antonio Vergari , Guy Van den Broeck

Compositional data are commonly known as multivariate observations carrying relative information. Even though the case of vector or even two-factorial compositional data (compositional tables) is already well described in the literature,…

Methodology · Statistics 2022-01-26 Kamila Fačevicová , Peter Filzmoser , Karel Hron

We introduce structured decompositions, category-theoretic structures which simultaneously generalize notions from graph theory (including treewidth, layered treewidth, co-treewidth, graph decomposition width, tree independence number,…

Category Theory · Mathematics 2025-05-21 Benjamin Merlin Bumpus , Zoltan A. Kocsis , Jade Edenstar Master , Emilio Minichiello

We introduce a novel technique for checking reachability in Petri nets that relies on a recently introduced compositional algebra of nets. We prove that the technique is correct, and discuss our implementation. We report promising…

Logic in Computer Science · Computer Science 2014-04-22 Paweł Sobocinski , Owen Stephens

In this article, we survey the primary research on polyhedral computing methods for constrained linear control systems. Our focus is on the modeling power of convex optimization, featured to design set-based robust and optimal controllers.…

Optimization and Control · Mathematics 2024-12-18 Boris Houska , Matthias A. Müller , Mario E. Villanueva