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Pull-tabbing is an evaluation approach for functional logic computations, based on a graph transformation recently proposed, which avoids making irrevocable non-deterministic choices that would jeopardize the completeness of computations.…

Programming Languages · Computer Science 2011-08-02 Sergio Antoy

Ordered, linear, and other substructural type systems allow us to expose deep properties of programs at the syntactic level of types. In this paper, we develop a family of unary logical relations that allow us to prove consequences of…

Logic in Computer Science · Computer Science 2025-03-06 C. B. Aberlé , Chris Martens , Frank Pfenning

The problems of computational data processing involving regression, interpolation, reconstruction and imputation for multidimensional big datasets are becoming more important these days, because of the availability of data and their widely…

Methodology · Statistics 2017-03-22 Yuri K. Shestopaloff , Alexander Y. Shestopaloff

In this paper, we consider situations in which a given logical function is realized by a multithreshold threshold function. In such situations, constant functions can be easily obtained from multithreshold threshold functions, and…

Neural and Evolutionary Computing · Computer Science 2013-01-03 Yukihiro Kamada , Kiyonori Miyasaki

Bottom-up knowledge compilation is a paradigm for generating representations of functions by iteratively conjoining constraints using a so-called apply function. When the input is not efficiently compilable into a language - generally a…

Computational Complexity · Computer Science 2021-12-24 Alexis de Colnet , Stefan Mengel

This paper introduces a new functional expansion framework that extends classical ideas beyond the Taylor series. Unlike traditional Taylor expansions based on local polynomial approximations, the proposed approach arises from exact…

Numerical Analysis · Mathematics 2026-02-03 Junping Wang

Cortical networks are strongly recurrent, and neurons have intrinsic temporal dynamics. This sets them apart from deep feed-forward networks. Despite the tremendous progress in the application of feed-forward networks and their theoretical…

Disordered Systems and Neural Networks · Physics 2021-07-14 Sandra Nestler , Christian Keup , David Dahmen , Matthieu Gilson , Holger Rauhut , Moritz Helias

Higher-order probabilistic programming languages allow programmers to write sophisticated models in machine learning and statistics in a succinct and structured way, but step outside the standard measure-theoretic formalization of…

Programming Languages · Computer Science 2020-12-03 Chris Heunen , Ohad Kammar , Sam Staton , Hongseok Yang

High-dimensional neural activity often reside in a low-dimensional subspace, referred to as neural manifolds. Grid cells in the medial entorhinal cortex provide a periodic spatial code that are organized near a toroidal manifold,…

Neurons and Cognition · Quantitative Biology 2025-10-22 Yuxing Jared Yao , Iris H. R. Yoon

We introduce succinct lossless representations of query results called covers. They are subsets of the query results that correspond to minimal edge covers in the hypergraphs of these results. We first study covers whose structures are…

Databases · Computer Science 2018-01-12 Ahmet Kara , Dan Olteanu

A reconstruction problem is formulated for multisets over commutative groupoids. The cards of a multiset are obtained by replacing a pair of its elements by their sum. Necessary and sufficient conditions for the reconstructibility of…

Combinatorics · Mathematics 2016-11-22 Erkko Lehtonen

Recursive (looped) Transformers decouple computational depth from parameter depth by repeatedly applying shared layers, providing an explicit architectural primitive for iterative refinement and latent reasoning. However, early looped…

Machine Learning · Computer Science 2026-04-21 Chengting Yu , Xiaobo Shu , Yadao Wang , Yizhen Zhang , Haoyi Wu , You Wu , Rujiao Long , Ziheng Chen , Yuchi Xu , Wenbo Su , Bo Zheng

A collection of algorithms in object-oriented MATLAB is described for numerically computing with smooth functions defined on the unit ball in the Chebfun software. Functions are numerically and adaptively resolved to essentially machine…

Numerical Analysis · Mathematics 2020-09-29 Nicolas Boullé , Alex Townsend

We introduce a novel embedding method diverging from conventional approaches by operating within function spaces of finite dimension rather than finite vector space, thus departing significantly from standard knowledge graph embedding…

Machine Learning · Statistics 2024-09-25 Louis Mozart Kamdem Teyou , Caglar Demir , Axel-Cyrille Ngonga Ngomo

Determining the approximate degree composition for Boolean functions remains a significant unsolved problem in Boolean function complexity. In recent decades, researchers have concentrated on proving that approximate degree composes for…

Computational Complexity · Computer Science 2025-01-22 Sourav Chakraborty , Chandrima Kayal , Rajat Mittal , Manaswi Paraashar , Nitin Saurabh

Patterns are fundamental to human cognition, enabling the recognition of structure and regularity across diverse domains. In this work, we focus on structural repeats, patterns that arise from the repetition of hierarchical relations within…

Computation and Language · Computer Science 2025-04-15 Zeng Ren , Xinyi Guan , Martin Rohrmeier

The rapid growth of large models' size has far outpaced that of computing resources. To bridge this gap, encouraged by the parsimonious relationship between genotype and phenotype in the brain's growth and development, we propose the…

Machine Learning · Computer Science 2026-02-04 Fenglei Fan , Juntong Fan , Dayang Wang , Jingbo Zhang , Zelin Dong , Shijun Zhang , Ge Wang , Tieyong Zeng

We propose that protein loops can be interpreted as topological domain-wall solitons. They interpolate between ground states that are the secondary structures like alpha-helices and beta-strands. Entire proteins can then be folded simply by…

Biological Physics · Physics 2014-11-20 M. N. Chernodub , Shuangwei Hu , Antti J. Niemi

A solution is proposed for the problem of composition of ordinary generating functions. A new class of functions that provides a composition of ordinary generating functions is introduced; main theorems are presented; compositae are written…

Combinatorics · Mathematics 2010-09-15 Kruchinin Vladimir Victorovich

We address the problem of generating a high-resolution surface reconstruction from a single image. Our approach is to learn a Higher Order Function (HOF) which takes an image of an object as input and generates a mapping function. The…

Computer Vision and Pattern Recognition · Computer Science 2019-12-20 Ziyun Wang , Volkan Isler , Daniel D. Lee