1 code implementation • 23 Oct 2023 • Alex D. Richardson, Tibor Antal, Richard A. Blythe, Linus J. Schumacher
Being able to learn arbitrary dynamics gives NCA great potential as a data driven modelling framework, especially for modelling biological pattern formation.
no code implementations • 25 May 2023 • Juan Guerrero Montero, Andres Karjus, Kenny Smith, Richard A. Blythe
Language change is a cultural evolutionary process in which variants of linguistic variables change in frequency through processes analogous to mutation, selection and genetic drift.
no code implementations • 8 Mar 2023 • Juan Guerrero Montero, Richard A. Blythe
We construct a reliable estimation of evolutionary parameters within the Wright-Fisher model, which describes changes in allele frequencies due to selection and genetic drift, from time-series data.
1 code implementation • 19 Mar 2021 • Andres Karjus, Richard A. Blythe, Simon Kirby, Tianyu Wang, Kenny Smith
Colexification refers to the phenomenon of multiple meanings sharing one word in a language.
1 code implementation • 16 Jun 2020 • Andres Karjus, Richard A. Blythe, Simon Kirby, Kenny Smith
By contrast, in topics which are increasing in importance for language users, near-synonymous words tend not to compete directly and can coexist.
no code implementations • 27 Apr 2020 • Liam J. Ruske, Jochen Kursawe, Anestis Tsakiridis, Valerie Wilson, Alexander G. Fletcher, Richard A. Blythe, Linus J. Schumacher
For both culture conditions, our inference supports the model where cell state transitions are coupled to division.
Cultural Vocal Bursts Intensity Prediction Experimental Design +1
1 code implementation • 3 Nov 2018 • Andres Karjus, Richard A. Blythe, Simon Kirby, Kenny Smith
Newberry et al. (Detecting evolutionary forces in language change, Nature 551, 2017) tackle an important but difficult problem in linguistics, the testing of selective theories of language change against a null model of drift.
no code implementations • 28 Sep 2018 • James Holehouse, Richard A. Blythe
Cross-situational word learning, wherein a learner combines information about possible meanings of a word across multiple exposures, has previously been shown to be a very powerful strategy to acquire a large lexicon in a short time.
1 code implementation • 2 Jun 2018 • Andres Karjus, Richard A. Blythe, Simon Kirby, Kenny Smith
In this work, we introduce a simple model for controlling for topical fluctuations in corpora - the topical-cultural advection model - and demonstrate how it provides a robust baseline of variability in word frequency changes over time.
no code implementations • 1 May 2015 • Richard A. Blythe
Methods and insights from statistical physics are finding an increasing variety of applications where one seeks to understand the emergent properties of a complex interacting system.
no code implementations • 8 Dec 2014 • Richard A. Blythe, Andrew D. M. Smith, Kenny Smith
Language learners must learn the meanings of many thousands of words, despite those words occurring in complex environments in which infinitely many meanings might be inferred by the learner as a word's true meaning.
no code implementations • 22 Feb 2013 • Rainer Reisenauer, Kenny Smith, Richard A. Blythe
We study the time taken by a language learner to correctly identify the meaning of all words in a lexicon under conditions where many plausible meanings can be inferred whenever a word is uttered.