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Found 12 papers, 5 papers with code
Learning spatio-temporal patterns with Neural Cellular Automata
Being able to learn arbitrary dynamics gives NCA great potential as a data driven modelling framework, especially for modelling biological pattern formation.
Reliable Detection and Quantification of Selective Forces in Language Change
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.
Self-contained Beta-with-Spikes Approximation for Inference Under a Wright-Fisher Model
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.
Conceptual similarity and communicative need shape colexification: an experimental study
Colexification refers to the phenomenon of multiple meanings sharing one word in a language.
Communicative need modulates competition in language change
By contrast, in topics which are increasing in importance for language users, near-synonymous words tend not to compete directly and can coexist.
Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots
For both culture conditions, our inference supports the model where cell state transitions are coupled to division.
Cultural Vocal Bursts Intensity Prediction
Experimental Design
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Challenges in detecting evolutionary forces in language change using diachronic corpora
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.
Cross-situational learning of large lexicons with finite memory
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.
Quantifying the dynamics of topical fluctuations in language
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.
Hierarchy of Scales in Language Dynamics
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.
Word learning under infinite uncertainty
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.
Stochastic dynamics of lexicon learning in an uncertain and nonuniform world
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.
