tdhoffman

tdhoffman's Stars

• poteto/hiring-without-whiteboards

  ⭐️ Companies that don't have a broken hiring process

  Language:JavaScript46.9k86903.6k

• rasbt/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  Language:Jupyter Notebook16.8k594304k

• exaloop/codon

  A high-performance, zero-overhead, extensible Python compiler using LLVM

  Language:C++15.2k137428522

• dunovank/jupyter-themes

  Custom Jupyter Notebook Themes

  Language:CSS9.8k1563991.1k

• sacridini/Awesome-Geospatial

  Long list of geospatial tools and resources

  4.2k20419630

• pysal/pysal

  PySAL: Python Spatial Analysis Library Meta-Package

  Language:Python1.3k79651302

• deepVector/geospatial-machine-learning

  A curated list of resources focused on Machine Learning in Geospatial Data Science.

  579421149

• DataForScience/Causality

  Language:Jupyter Notebook464320100

• matthewwardrop/formulaic

  A high-performance implementation of Wilkinson formulas for Python.

  Language:Python3561211325

• zenna/Omega.jl

  Causal, Higher-Order, Probabilistic Programming

  Language:Julia1641314317

• rmcelreath/PhD_planning_template

  Outline for planning PhD projects

  Language:TeX1086117

• JingyuHe/XBART

  Language:C++89131225

• raunakkmr/GraphSAGE-and-GAT-for-link-prediction

  GraphSAGE and GAT for link prediction.

  Language:Jupyter Notebook823418

• ConnorDonegan/geostan

  Bayesian spatial analysis

  Language:R784136

• cmu-phil/example-causal-datasets

  Example causal datasets with consistent formatting and ground truth

  704411

• dizhu-gis/SRGCNN

  Spatial regression graph convolutional neural networks: Spatial regression analysis conducted in the manner of graph convolutional neural network. Two versions of SRGCNN model are provided in the initial post: a) global regression model (SRGCNN) and b) geographically weighted regression model (SRGCNN-GW)

  Language:Jupyter Notebook511111

• ljwolf/wampl

  Another Wes Anderson palette implementation

  Language:Jupyter Notebook27445

• michaelpollmann/spatialTreat-example

  a simple example for estimating the causal effects of spatial treatments, following Pollmann (2021)

  Language:HTML24119

• javierbarbero/SpatialDependence.jl

  A Julia package for spatial dependence (spatial autocorrelation), spatial weights matrices, and exploratory spatial data analysis (ESDA).

  Language:Julia12130

• gpapadog/Interference

  IPW estimators of causal effect estimands in the presence of interference

  Language:R9402

• warrenjl/KDExp

  Kernel Density Estimation Prior Distribution for Exposure Uncertainty Propagation

  Language:C++2201

• gpapadog/Bipartite_Interference

  Language:R1320