Scientific-ML's repositories
lecture-source-jl
Source files for "Lectures in Quantitative Economics" -- Julia version
6S083
Materials for MIT 6.S083 / 18.S190: Computational thinking with Julia + application to the COVID-19 pandemic
Strategems.jl
Quantitative systematic trading strategy development and backtesting in Julia
Surrogates.jl
Surrogate modeling and optimization
Stheno.jl
Probabilistic Programming with Gaussian processes in Julia
DataStructures.jl
Julia implementation of Data structures
XGBoost.jl
XGBoost Julia Package
DiffEqTutorials.jl
Tutorials for using the DiffEq ecosystem
DiffEqBenchmarks.jl
Benchmarks for the DiffEq Solvers
sciml-papers
Collection of papers and references for scientific machine learning techniques and applications
18S096SciML
18.S096 - Applications of Scientific Machine Learning
18337
18.337 - Parallel Computing and Scientific Machine Learning
IntroToJulia
A Deep Introduction to Julia for Data Science and Scientific Computing
Neural-ODE-Experiments
This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data
Mocha.jl
Deep Learning framework for Julia