francois-rozet / diffusion-priors
Learning Diffusion Priors from Observations by Expectation Maximization
☆19Updated 3 months ago
Related projects ⓘ
Alternatives and complementary repositories for diffusion-priors
- Sliced Iterative Generator (SIG) & Gaussianizing Iterative Slicing (GIS)☆36Updated last year
- Generative models with JAX.☆18Updated 10 months ago
- Differentiable and accelerated wavelet transform on the sphere with JAX☆15Updated 7 months ago
- A repository to store state of the art score model architectures☆44Updated this week
- Simulation-based inference in JAX☆21Updated last month
- ☆22Updated 4 years ago
- Stainless neural networks in JAX☆31Updated last month
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆44Updated 5 months ago
- Differentiable and gpu enabled fast wavelet transforms in JAX.☆40Updated 4 months ago
- Probabilistic modeling of tabular data with normalizing flows.☆55Updated 5 months ago
- Coverage tests to check the quality of your posterior estimators.☆27Updated 3 months ago
- JAX-based linear Einstein-Boltzmann solver for cosmology☆12Updated last month
- Code for Gaussian Score Matching Variational Inference☆28Updated last month
- Unleash the true power of scheduling☆24Updated this week
- A simple implementation of Hamiltonian Monte Carlo in JAX.☆16Updated 9 months ago
- Community-sourced list of papers and resources on neural simulation-based inference.☆96Updated 5 months ago
- ☆19Updated last year
- A package to describe amortized (conditional) normalizing-flow PDFs defined jointly on tensor products of manifolds with coverage control…☆42Updated 9 months ago
- ☆13Updated last year
- Likelihood-free AMortized Posterior Estimation with PyTorch☆119Updated 3 months ago
- Gradient Based Nested Sampling☆17Updated 9 months ago
- Normalizing Flows with a resampled base distribution☆44Updated 2 years ago
- ☆16Updated 3 years ago
- Transformer-guided diffusion for galaxy clustering. Code repository associated with https://arxiv.org/abs/2311.17141☆21Updated 10 months ago
- Bayesian Uncertainty Quantification by Deep Generative Model☆19Updated 4 years ago
- Using neural networks to extract sufficient statistics from data by maximising the Fisher information☆30Updated last year
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆90Updated 7 months ago
- Exploring how ChatGPT can be used to accelerate research in cosmology.☆12Updated last year
- Material for the CMU Quarks2Cosmos Conference Data Challenges☆14Updated last year
- 🚀 A powerful library for efficient training of Neural Fields at scale.☆27Updated 9 months ago