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Tilman Troester's Projects

1dcosmo icon 1dcosmo

N-body code in Python for one-dimensional cosmological simulations of structure formation.

baryon_painter icon baryon_painter

Painting baryons on N-body simulations with deep generative models

camb icon camb

Code for Anisotropies in the Microwave Background

ccimport icon ccimport

a tiny package for fast python c++ binding build.

cumm icon cumm

CUda Matrix Multiply library.

dypolychord icon dypolychord

Super fast dynamic nested sampling with PolyChord (Python, C++ and Fortran likelihoods).

emcee icon emcee

The Python ensemble sampling toolkit for affine-invariant MCMC

f90wrap icon f90wrap

F90 to Python interface generator with derived type support

getdist icon getdist

MCMC sample analysis, kernel densities, plotting, and GUI

grftools icon grftools

Collection of tools for dealing with Gaussian random fields

hmx icon hmx

Halo-model cross-correlation code

kids-1000xtsz icon kids-1000xtsz

Pseudo-Cl analysis of KiDS-1000 gravitational lensing and its cross-correlation with the thermal Sunyaev-Zeldovich effect

n5k icon n5k

Non-local No-Nonsense Non-Limber Numerical Knockout

nestcheck icon nestcheck

Error analysis, diagnostic tests and plots for nested sampling calculations.

nsf icon nsf

Code for Neural Spline Flows paper

polychordlite icon polychordlite

Public version of PolyChord: See polychord.co.uk for PolyChordPro

py3nj icon py3nj

Wigner's 3J, 6J, 9J symbols for python

pycl2xi icon pycl2xi

Python wrapper around FFTLog to calculate 2D correlation functions from angular power spectra.

pydelfi icon pydelfi

Density Estimation Likelihood-Free Inference with neural density estimators and adaptive acquisition of simulations

pyhmcode icon pyhmcode

Augmented halo model for accurate non-linear matter power spectrum calculations

rosenblatt icon rosenblatt

Code implementing methods from paper "Properties and numerical evaluation of the Rosenblatt distribution"

simplicial_neural_networks icon simplicial_neural_networks

Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes.

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