pyro-ppl / pyroedLinks
Bayesian optimization of discrete sequences
☆21Updated 3 years ago
Alternatives and similar repositories for pyroed
Users that are interested in pyroed are comparing it to the libraries listed below
Sorting:
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Pre-trained Gaussian processes for Bayesian optimization☆92Updated 2 months ago
- Bayesian algorithm execution (BAX)☆49Updated 3 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- probabilistic programming focused on fun☆41Updated 8 months ago
- Generic API for dispatch to Pyro backends.☆16Updated 3 years ago
- Inference Combinators in JAX☆49Updated last month
- Minimal Implementation of Bayesian Optimization in JAX☆95Updated 2 months ago
- Graph Learning with JAX☆14Updated 2 years ago
- Exponential families for JAX☆71Updated this week
- ☆30Updated 9 months ago
- Tools for JAX☆47Updated last week
- A generic interface for linear algebra backends☆73Updated 3 months ago
- Normalizing Flows using JAX☆83Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Efficient, lightweight variational inference and approximation bounds☆43Updated last year
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆34Updated 4 years ago
- Bayesian inference with Python and Jax.☆32Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Probabilistic deep learning using JAX☆14Updated 4 months ago
- Bayesian inference for a logistic regression model in various languages☆42Updated last year
- "Variational inference tools to leverage estimator sensitivity."☆16Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Learning with operator-valued kernels☆22Updated 2 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Jax SSM Library☆49Updated 2 years ago
- AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.☆39Updated last year