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Neural codes form an algebraic framework to study the nervous system, and understanding neural codes is a key goal of mathematical neuroscience. Neural rings and ideals are the tools connecting neuroscience and commutative algebra. In this…

Commutative Algebra · Mathematics 2025-11-25 Trung Chau

We describe a novel extension of subspace codes for noncoherent networks, suitable for use when the network is viewed as a communication system that introduces both dimension and symbol errors. We show that when symbol erasures occur in a…

Information Theory · Computer Science 2012-09-25 Vitaly Skachek , Olgica Milenkovic , Angelia Nedic

The neural coding is yet to be discovered. The neuronal operational modes that arise with fixed inputs but with varying degrees of stimulation help to elucidate their coding properties. In neurons receiving {\it in vivo} stimulation, we…

Neurons and Cognition · Quantitative Biology 2025-11-05 Lindsey Knowles , Cesar Ceballos , Rodrigo Pena

Lascoux polynomials are a class of nonhomogeneous polynomials which form a basis of the full polynomial ring. Recently, Pan and Yu showed that Lascoux polynomials can be defined as generating polynomials for certain collections of diagrams…

Combinatorics · Mathematics 2024-10-08 Kelsey Hanser , Nicholas Mayers

Humans have the ability to rapidly understand rich combinatorial concepts from limited data. Here we investigate this ability in the context of auditory signals, which have been evolved in a cultural transmission experiment to study the…

Computation and Language · Computer Science 2021-04-19 Matthias Hofer , Tuan Anh Le , Roger Levy , Josh Tenenbaum

Optical orthogonal codes (OOCs) are sets of $(0,1)$-sequences with good auto- and cross-correlation properties. They were originally introduced for use in multi-access communication, particularly in the setting of optical CDMA…

Combinatorics · Mathematics 2025-01-15 Sophie Huczynska , Siaw-Lynn Ng

A barcode is a finite multiset of intervals on the real line, $B = \{ (b_i, d_i)\}_{i=1}^n$. Barcodes are important objects in topological data analysis, where they serve as summaries of the persistent homology groups of a filtration. The…

Combinatorics · Mathematics 2022-09-14 Edgar Jaramillo-Rodriguez

We propose a new family of combinatorial inference problems for graphical models. Unlike classical statistical inference where the main interest is point estimation or parameter testing, combinatorial inference aims at testing the global…

Statistics Theory · Mathematics 2018-02-14 Matey Neykov , Junwei Lu , Han Liu

Two tantalizing invariants of a combinatorial code $\mathcal C\subseteq 2^{[n]}$ are cdim$(\mathcal C)$ and odim$(\mathcal C)$, the smallest dimension in which $\mathcal C$ can be realized by convex closed or open sets, respectively. Cruz,…

Combinatorics · Mathematics 2022-07-19 R. Amzi Jeffs

The paper deals with combinatorial and stochastic structures of cubical token systems. A cubical token system is an instance of a token system, which in turn is an instance of a transition system. It is shown that some basic results of…

Combinatorics · Mathematics 2007-05-23 Sergei Ovchinnikov

Predictive coding is an influential theory of cortical function which posits that the principal computation the brain performs, which underlies both perception and learning, is the minimization of prediction errors. While motivated by…

Neurons and Cognition · Quantitative Biology 2020-10-13 Beren Millidge , Alexander Tschantz , Anil Seth , Christopher L Buckley

In recent years, there has been a growing interest in using learning-based approaches for solving combinatorial problems, either in an end-to-end manner or in conjunction with traditional optimization algorithms. In both scenarios, the…

Machine Learning · Computer Science 2024-03-14 Léo Boisvert , Hélène Verhaeghe , Quentin Cappart

In physics we often use very simple models to describe systems with many degrees of freedom, but it is not clear why or how this success can be transferred to the more complex biological context. We consider models for the joint…

Neurons and Cognition · Quantitative Biology 2024-12-06 Luisa Ramirez , William Bialek , Stephanie E. Palmer , David J. Schwab

This paper presents the input convex neural network architecture. These are scalar-valued (potentially deep) neural networks with constraints on the network parameters such that the output of the network is a convex function of (some of)…

Machine Learning · Computer Science 2017-06-15 Brandon Amos , Lei Xu , J. Zico Kolter

Neural networks are capable of superposition -- representing more features than there are dimensions. Recent work considers the analogous concept for computation instead of storage, proposing theoretical constructions. But there has been…

Machine Learning · Computer Science 2025-07-15 Adam Newgas

It is a fundamental behavior that different individuals see the world in a largely similar manner. This is an essential basis for humans' ability to cooperate and communicate. However, what are the neuronal properties that underlie these…

Neurons and Cognition · Quantitative Biology 2024-07-12 Ofer Lipman , Shany Grossman , Doron Friedman , Yacov Hel-Or , Rafael Malach

Small neural networks (NNs) used for error correction were shown to improve on classic channel codes and to address channel model changes. We extend the code dimension of any such structure by using the same NN under one-hot encoding…

Information Theory · Computer Science 2023-04-03 Onur Günlü , Rick Fritschek , Rafael F. Schaefer

A barcode is a finite multiset of intervals on the real line. Jaramillo-Rodriguez (2023) previously defined a map from the space of barcodes with a fixed number of bars to a set of multipermutations, which presented new combinatorial…

Combinatorics · Mathematics 2023-12-15 Alex Bouquet , Andrés R. Vindas-Meléndez

Multitriangulations, and more generally subword complexes, yield a large family of simplicial complexes that are homeomorphic to spheres. Until now, all attempts to prove or disprove that they can be realized as convex polytopes faced major…

Combinatorics · Mathematics 2021-05-07 Jean-Philippe Labbé

The cut polytope ${\rm CUT}(n)$ is the convex hull of the cut vectors in a complete graph with vertex set $\{1,\ldots,n\}$. It is well known in the area of combinatorial optimization and recently has also been studied in a direct relation…

Discrete Mathematics · Computer Science 2018-12-11 Nevena Maric
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