Moritz Schauer
You find me via e-mail (see my university contact information on http://www.math.chalmers.se/~smoritz/index.html) or on JuliaLang's Community Channels, e.g. Zulip or Slack (see, https://julialang.org/community/).
Name: Moritz Schauer
Type: User
Company: University of Gothenburg and Chalmers Technical University
Bio: Statistician, PhD
Twitter: moritzschauer
Location: Gothenburg
Moritz Schauer
You find me via e-mail (see my university contact information on http://www.math.chalmers.se/~smoritz/index.html) or on JuliaLang's Community Channels, e.g. Zulip or Slack (see, https://julialang.org/community/).
An abstract interface for plotting libraries
Robust implementation for random-walk Metropolis-Hastings algorithms
A Latex style and template for paper preprints (based on NIPS style)
Backward filtering for a SIR model
A collection of Julia benchmarks available for CI tracking from the JuliaLang/julia repository
Code accompanying the paper Frank van der Meulen, Moritz Schauer: Bayesian estimation of discretely observed multi-dimensional diffusion processes using guided proposals
Sample from nonparametric posterior
Blog posts
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
A thin wrapper over Bridge.jl to add it to the common interface
Image analysis and stochastic processes on shape and landmark spaces.
Inference for diffusion processes with the use of `Guided Proposals`
Stochastic partial differential equations with Bridge.jl
Full-featured traits in Julia. Without full features how dare I say this?
Overdub Your Julia Code
Causal inference, graphical models and structure learning in Julia
AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.
An experimental language for causal reasoning
Stochastic Gradients of discrete random quantities
Color manipulation utilities for Julia
Contributor's Guide on Collaborative Practices for Community Packages
A combinatorics library for Julia
cross-version compatibility
Staging package for new compiler interfaces
Agent Based Model for COVID 19 transmission dynamics
The Julia C++ Interface
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.