Moritz Schauer
mschauer
Statistician, PhD
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Top Repositories
Causal inference, graphical models and structure learning in Julia
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection
Flexible filtering and smoothing in Julia
Automatic probabilistic programming for scientific machine learning and dynamical models
Iterators with message passing and feedback loops
Repositories
149Causal inference, graphical models and structure learning in Julia
Nonparametric Bayesian volatility learning under microstructure noise
Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection
Statistical inference for Poisson Processes
These slides are from a guest lecture on causal discovery. They show how independence patterns, Gaussian SEMs, and interventions constrain causal structure. No prior causal inference background assumed.
No description provided.
A curated list of awesome Category Theory resources.
Automatic probabilistic programming for scientific machine learning and dynamical models
Tour through non-parametric Bayesian regression in Fourier domain using Julia https://mschauer.github.io/nonparbayes/
Guided smoothing and control for diffusion processes
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Stan website based on the So Simple Jekyll theme.
Image analysis and stochastic processes on shape and landmark spaces.
++ incorporated into https://github.com/JuliaLang/IterativeSolvers.jl ++ Induced Dimension Reduction method IDR(s) for solving general non-symmetric linear equations using a Krylov method, for example ordinary linear equations or Sylvester and Stein equations.
Statistics for Structures Seminar
Flexible filtering and smoothing in Julia
Backward-filtering forward-guiding with StochasticDiffEq.jl
Community document on Gaussian conditional distributions (draft, LaTeX)
Iterators with message passing and feedback loops
Gaussian distributions as state variables and for uncertainty quantification with Unitful
Generalized golden sequences, a form of low discrepancy sequence or quasi random numbers
No description provided.
A logarithmic number system for Julia.
An experimental language for causal reasoning
📝 A nicely formatted LaTeX preprint template
LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
Backward filtering for a SIR model
Matlab code for UAI2022 paper "Greedy Equivalence Search in the Presence of Latent Confounders"
Blog posts
Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.