adamlauretig
Data Scientist. Interested in text as data/NLP, Bayesian statistics, and causal inference.
Pinned Repositories
AMEN_models_in_stan
Implementation of Shahryar Minhas, Peter Hoff, and Mike Ward's AMEN models for network data in stan
bwe
Implements the model described in "Identification, Interpretability, and Bayesian Word Embeddings"
bwe_application_naacl_2019
Replication materials for "Identification, Interpretability, and Bayesian Word Embeddings"
gensim_in_R
Code for estimating word embeddings with gensim in R.
icews_python
Code to convert ICEWS data into pandas Dataframes. Based on https://github.com/openeventdata/text_to_CAMEO
ny_r_talk
Slides and Code for NY R Users Meetup on January 9, 2020, "A Common Model, Separated by Two Disciplines: Bayesian Factorization Machines with Stan and R" presented by Adam Lauretig
pymc_bart
Experimenting w/the new BART function in PYMC
rmarkdown_resources
Resources used to introduce undergraduates to R markdown, from Ohio State's POL4782, spring 2018.
Unity_Intro
An introduction to R on the Unity HPC cluster at Ohio State
adamlauretig's Repositories
adamlauretig/bwe
Implements the model described in "Identification, Interpretability, and Bayesian Word Embeddings"
adamlauretig/AMEN_models_in_stan
Implementation of Shahryar Minhas, Peter Hoff, and Mike Ward's AMEN models for network data in stan
adamlauretig/ny_r_talk
Slides and Code for NY R Users Meetup on January 9, 2020, "A Common Model, Separated by Two Disciplines: Bayesian Factorization Machines with Stan and R" presented by Adam Lauretig
adamlauretig/Unity_Intro
An introduction to R on the Unity HPC cluster at Ohio State
adamlauretig/pymc_bart
Experimenting w/the new BART function in PYMC
adamlauretig/bwe_application_naacl_2019
Replication materials for "Identification, Interpretability, and Bayesian Word Embeddings"
adamlauretig/gensim_in_R
Code for estimating word embeddings with gensim in R.
adamlauretig/quant_1_code
Code for POL 7551 Fall 2018. The first graduate course in methodology for political science at Ohio State.
adamlauretig/rmarkdown_resources
Resources used to introduce undergraduates to R markdown, from Ohio State's POL4782, spring 2018.
adamlauretig/OSU_brand_slides
OSU branded beamer + rmarkdown slides
adamlauretig/academic-kickstart
📝 Easily create a beautiful website using Academic, Hugo, and Netlify
adamlauretig/Prism_presentation
Code for Presentation on Spatial Statistics
adamlauretig/icews_python
Code to convert ICEWS data into pandas Dataframes. Based on https://github.com/openeventdata/text_to_CAMEO
adamlauretig/adamlauretig.github.io
adamlauretig/annontated_sam
adamlauretig/CRAN_total_correlation
Examining the total correlation among packages on CRAN.
adamlauretig/curbed_500_data
dataset taken from https://www.curbed.com/article/nyc-businesses-closed-2020-pandemic.html, curbed's 500 businesses closed during the pandemic
adamlauretig/example-models
Example models for Stan
adamlauretig/factorization_machines
A simple Bayesian factorization machine implementation in stan.
adamlauretig/first_year_workshop
Code for the first year workshop, installing R/LaTeX
adamlauretig/nyc_recs
various nyc restaurant recs
adamlauretig/ohio-state-coe-dissertation-template
LaTeX template for help with writing CSE dissertation at Ohio State University
adamlauretig/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
adamlauretig/Quant-3-Lecture-Code
Code for Lecture on Optimizing R code
adamlauretig/simulate_gps
Code for a blogpost simulation study of Generalized Propensity Scores and Marginal Structural Models
adamlauretig/skip-gram-tensor
Code related to "Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis"
adamlauretig/Statistics_and_International_Security
Code for OUP IS Handbook chapter
adamlauretig/tf-decompose
Tensor decomposition implemented in TensorFlow
adamlauretig/thoughts_on_leaving_academia
some thoughts on leaving academia after a while
adamlauretig/wordVectors
An R package for creating and exploring word2vec and other word embedding models