DifferentiableUniverseInitiative / JaxPM
JAX-powered Cosmological Particle-Mesh N-body Solver
☆37Updated last month
Alternatives and similar repositories for JaxPM:
Users that are interested in JaxPM are comparing it to the libraries listed below
- Curated list of astronomy/astrophysics code packages using JAX☆38Updated 4 months ago
- Unitful Quantities in JAX☆34Updated last week
- JAX-based linear Einstein-Boltzmann solver for cosmology☆16Updated last week
- nessai: Nested Sampling with Artificial Intelligence☆38Updated this week
- A python package for Weak Lensing Implicit Inference with Differentiable Simulator☆14Updated last year
- Differentiable Cosmological Forward Model☆78Updated last month
- Astronomy Research + JAX Meeting 2024☆13Updated 5 months ago
- JAX Tutorial notebooks : basics, crash & tips, usage of optax/JaxOptim/Numpyro☆14Updated last month
- Package for Neural Posterior Estimation and Importance Sampling focused on Astronomical Applications☆37Updated last month
- Differentiable Likelihood for CMB Analysis☆18Updated 2 weeks ago
- Coverage tests to check the quality of your posterior estimators.☆30Updated 8 months ago
- Robust ML in Astro☆53Updated this week
- Gradient Based Nested Sampling☆20Updated last year
- ☆16Updated 4 years ago
- JAX port of GalSim, for parallelized, GPU accelerated, and differentiable galaxy image simulations.☆29Updated this week
- Differentiable Gravitational Waveforms with JAX☆56Updated 7 months ago
- A fast, differentiable, and extensible public BBN code☆11Updated last month
- CPU/GPU agnostic gravitational-wave population inference☆45Updated this week
- Generator for Large Scale Structure☆38Updated this week
- Normalizing flow models allowing for a conditioning context, implemented using Jax, Flax, and Distrax.☆19Updated last year
- 🐈 Automatic differentiable spectrum modeling of exoplanets/brown dwarfs using JAX, compatible with NumPyro and Optax/JAXopt☆60Updated 2 weeks ago
- hankl is a lightweight Python implementation of the FFTLog algorithm for Cosmology☆24Updated 2 years ago
- Using Graph Neural Networks to regress baryonic properties directly from full dark matter merger trees.☆24Updated last year
- ☆13Updated last year
- Simulation-based (likelihood-free) inference customized for astronomical applications☆26Updated 5 months ago
- ☆22Updated this week
- Gravitational-wave data analysis tools in Jax☆68Updated this week
- Machine Learning - accelerated Bayesian inference☆68Updated 3 months ago
- Neural Network-Boosted Importance Nested Sampling for Bayesian Statistics☆83Updated 2 months ago
- Beyond-2pt blind data challenge☆16Updated 8 months ago