-
McGill University
- Montréal
- gottacatchenall.github.io
- @mdcatchen
- @michael@ecoevo.social
Starred repositories
A simulator for ecological dynamics written in Julia.
A Python library for fast, interactive geospatial vector data visualization in Jupyter.
A simulation engine for models related to plants
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset
The ultimate guide to distributed computing in Julia
Foundational tooling for handling collections of parameters in models
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Meta-package for data analysis in Julia, modeled after the R tidyverse.
Graph Neural Networks in Julia
Simple, blazing fast, transformer components.
Work with species distributions in Julia
Simulation, visualization, and inference of individual level infectious disease models with Julia
CAPTAIN is a Python program to optimize conservation planning based on biodiversity data and simulations using reinforcement learning
SLiM is a genetically explicit forward simulation software package for population genetics and evolutionary biology. It is highly flexible, with a built-in scripting language, and has a cross-platf…
Stochastic Optimization, Learning, Uncertainty and Sampling
Macros to define and implement interfaces, to ensure they are checked and correct.
Unicode-based scientific plotting for working in the terminal
🎓 Path to a free self-taught education in Computer Science!
Answers to 120 commonly asked data science interview questions.
population and community dynamics on spatial graphs, in julia. (formerly EcoDynamics.jl)
A shared Extent object for Julia spatial data, with DE-9IM spatial predicates
Examples of how to create colorful, annotated equations in Latex using Tikz.
Community Terrestrial Systems Model (includes the Community Land Model of CESM)
Simple layers for species distribution modeling and bioclimatic data
Grid-based approximation of partial differential equations in Julia