Nikola Surjanovic's repositories
AbstractMCMC.jl
Abstract types and interfaces for Markov chain Monte Carlo methods
AdvancedHMC.jl
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
arxiv-biorxiv-search
Python script to facilitate easy automatic pulling of new papers from Arxiv, Biorxiv, and Medrxiv with custom search features.
Joint-Seminar-Homepage
Code for the SFU/UBC Joint Statistics Seminar website. I am organizing this seminar as the President of the SFU Statistics and Actuarial Science Graduate Caucus, along with other graduate students.
Quantum-Computing
An Introduction to Quantum Computing for Statisticians. Includes code and my presentation materials.
blangSDK
Blang's software development kit
CLDA
Code for my STAT 548 report with Daniel McDonald. See also https://github.com/nikola-sur/LDA-Compression
DataStructures.jl
Julia implementation of Data structures
DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components
EvoTrees
R package wrapping EvoTrees.jl
Gaussian-Process-Regression
An Introduction to Kriging. Includes R code and my presentation materials.
Goodness-of-Fit-Examples
Examples of existing goodness-of-fit tests for logistic regression models. Includes some R code and presentation materials.
mcmcse.jl
A Julia port of the R package mcmcse
MCMCTempering.jl
Implementations of parallel and simulated tempering algorithms to augment samplers with tempering capabilities
miselect
Variable Selection for Multiply Imputed Data
nextflow-notes-nik
A template and short tutorial on nextflow for computational statisticians
SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
shortex
LaTeX header file with useful definitions
SortingAlgorithms.jl
extra sorting algorithms extending Julia's sorting API
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
ZigZagBoomerang.jl
Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection