mschauer

Moritz Schauer's starred repositories

Infiltrator.jl

No-overhead breakpoints in Julia

Language:JuliaMIT395 7 66

DiscoGrad

DiscoGrad - automatically differentiate across conditional branches in C++ programs

Language:C++MIT199 40

Yota.jl

Reverse-mode automatic differentiation in Julia

Language:JuliaMIT158 8 63

NetworkLayout.jl

Layout algorithms for graphs and trees in pure Julia.

Language:JuliaNOASSERTION97 11 24

moloch

A LaTeX Beamer theme, forked from the metropolis theme

Language:TeXCC-BY-SA-4.052 4 9

differentiable_mh

Code for paper https://arxiv.org/abs/2306.07961

Language:Julia51 60

ges

Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.

Language:PythonBSD-3-Clause48 2 2

SynthControl.jl

Synthetic control methods in Julia

Language:JuliaMIT35 4 18

Automates adjoints. Forward and reverse mode algorithmic differentiation around implicit functions (not propagating AD through), as well as custom rules to allow for mixed-mode AD or calling external (non-AD compatible) functions within an AD chain.

Language:JuliaMIT25 5 5

LowRankArithmetic.jl

Package for the propagation of representations of low-rank matrices through finite compositions of common operations.

Language:JuliaMIT22 1 1

KissSmoothing.jl

Easily smooth your data in Julia

Language:JuliaNOASSERTION22 1 2

RegressionAndOtherStories.jl

Data and functions to support Julia projects based on the book "Regression and Other Stories" by Andrew Gelman, Jennifer Hill and Aki Vehtari.

Language:PostScriptMIT22 2 1

causalAssembly

Language:PythonAGPL-3.020 3 3

ThreadedSparseArrays.jl

Language:JuliaMIT17 2 4

diff-evol-tree-search

We introduce a differentiable approach to phylogenetic tree construction, optimizing tree and ancestral sequences in its original representation itself, thus requiring no prior training data.

Language:Python17 20

MinimalPerfectHashes.jl

An implementation of minimal perfect hash function generation as described in Czech et. al. 1992.

Language:JuliaMIT16 182 7

Varsortability

Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https://arxiv.org/abs/2102.13647.

Language:PythonMIT14 40