Nikola Surjanovic's Projects
Abstract types and interfaces for Markov chain Monte Carlo methods
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Python script to facilitate easy automatic pulling of new papers from Arxiv, Biorxiv, and Medrxiv with custom search features.
Awesome resources on normalizing flows.
Adaptive Experimentation Platform
Implementation of normalising flows and constrained random variable transformations
Blang's software development kit
Bayesian optimization in PyTorch
BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
Code for my STAT 548 report with Daniel McDonald. See also https://github.com/nikola-sur/LDA-Compression
CmdStan, the command line interface to Stan
Code for first-order probabilistic programming to continuous normalizing flow compiler.
Julia implementation of Data structures
Julia implementation of Decision Tree (CART) and Random Forest algorithms
Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components
Filter design, periodograms, window functions, and other digital signal processing functionality
Implementation of domain-specific language (DSL) for dynamic probabilistic programming
Dynamic Nested Sampling package for computing Bayesian posteriors and evidences
R package wrapping EvoTrees.jl
My presentation for the Scientific Programming Study Group at SFU (slides in progress). "Let's Make Your R Code FastR: Part 1 (Introduction)"
An Introduction to Kriging. Includes R code and my presentation materials.
A general-purpose probabilistic programming system with programmable inference
A generalized Hosmer-Lemeshow goodness-of-fit test for a family of generalized linear models (GLMs)
Examples of existing goodness-of-fit tests for logistic regression models. Includes some R code and presentation materials.
Hypothesis tests for Julia