Mu-DS / practical_trainingLinks
Material for the MUDS Practical Data Science Training
☆15Updated 4 years ago
Alternatives and similar repositories for practical_training
Users that are interested in practical_training are comparing it to the libraries listed below
Sorting:
- Density Estimation Likelihood-Free Inference with neural density estimators and adaptive acquisition of simulations☆110Updated 2 years ago
- Likelihood-free AMortized Posterior Estimation with PyTorch☆131Updated last year
- Bayesian Uncertainty Quantification by Deep Generative Model☆19Updated 5 years ago
- Functions to compute conditional distributions of Gaussian mixture models.☆12Updated 6 months ago
- SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory☆23Updated 2 years ago
- A list of Python-based MCMC & ABC packages☆123Updated 5 months ago
- sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you nee…☆755Updated this week
- Simulation-based inference benchmark☆106Updated 10 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- ☆11Updated 2 years ago
- distributed, likelihood-free inference☆217Updated 4 months ago
- Unleash the true power of scheduling☆33Updated 7 months ago
- Implementation of Flexible Conditional Density Estimator☆25Updated 4 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆464Updated last year
- A system for scientific simulation-based inference at scale.☆164Updated last year
- multi-dimensional statistical test with python☆101Updated 11 months ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆74Updated 5 months ago
- Community-sourced list of papers and resources on neural simulation-based inference.☆135Updated 3 weeks ago
- Diagnostics for Conditional Density Estimators and Bayesian Inference Algorithms☆15Updated 3 years ago
- Conditional density estimation with neural networks☆34Updated 10 months ago
- Probabilistic modeling of tabular data with normalizing flows.☆58Updated last month
- ☆28Updated 2 years ago
- Normalizing-flow enhanced sampling package for probabilistic inference in Jax☆252Updated 3 weeks ago
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆132Updated 4 years ago
- ⚡️ zeus: Lightning Fast MCMC ⚡️☆241Updated last year
- A Python toolkit for (simulation-based) inference and the mechanization of science.☆53Updated 3 years ago
- Probabilistic Programming and Nested sampling in JAX☆211Updated last week
- ☆155Updated 3 years ago
- Gaussian processes in JAX and Flax.☆554Updated this week