shanest

decisions-games-ai

Lecture notes for a course on Decision and Game Theory for undergraduates studying AI

quantifier-rnn-learning

Accompanies the paper "Learnability and Semantic Universals" ; trains recurrent neural networks to learn to verify sentences with quantifiers in order to explain semantic universals

replicator_dynamic_examples

Simple code for running and visualizing replicator dynamics

color-learning

Accompanies the paper, "Ease of learning explains semantic universals". Generates and trains neural networks on artificial color systems, showing that _degree of convexity_ explains accuracy.

edugrad

A minimal re-implementation of the PyTorch API (forward/backward autodifferentiation), intended for pedagogical uses

allennlp-bert-example

function-words-context

Signaling games with function words amidst contextual variability

nn-tutorial

A tutorial introduction to neural networks, with an eye towards linguistic applications.

responsive-verbs

Accompanies the paper, "An Explanation of the Veridical Uniformity Universal"; trains neural networks to learn so-called responsive verbs in order to explain a semantic universal.

GodelBeta

Implementations of Godel's Beta Function in assorted languages

OntologyCV

Files for a computational biology project to extract a cardiovascular ontology from Foundational Model of Anatomy and use it to label a left ventricle atlas and then locate regions of interest in experiments.

SimInf_Quantifiers

learning-evolution-compositionality

Companion to the paper: Shane Steinert-Threlkeld, "Compositional Signaling in a Complex World", Journal of Logic, Language, and Information, vol 25 no 3, pp. 379-397 (DOI: 10.1007/s10849-016-9236-9)

neural-vision-most

Accompanies the paper "Neural Models of the Psychosemantics of 'most'": trains neural models of visual attention to replicate varoius cognitive tasks

scale-free-protest

Code for a project on relation between scaling parameter in scale-free networks and size of protests

ccg2mono

Take CCG parses and add monotonicity information on every constituent

fill-in-the-quant

Predict the most suitable quantifier for a given linguistic context

function-word-signaling

Code and data for paper (to be) submitted to JoLLI

jedi

Awesome autocompletion and static analysis library for python.

jedi-vim

Using the jedi autocompletion library for VIM.

mondrian

nlp-in-ling

Natural Language Processing Research in North American Linguistics Departments

non-trivial-modification

obsidian-clipper-bookmarklet

A bookmarklet that saves the current page and/or highlighted text to Obsidian.md

parseviz

Visualize constituent and dependency parses as PDF or image formats, through GraphViz.

python-tutorial-clms

Short Python tutorial for CLMS orientation

shanest.github.io

SimInf_Quantifiers_forked

stringer

Package of utilities for working with Strings in Mojo

tensorflow

Computation using data flow graphs for scalable machine learning