ziatdinovmax / gpaxLinks
Gaussian Processes for Experimental Sciences
☆227Updated last month
Alternatives and similar repositories for gpax
Users that are interested in gpax are comparing it to the libraries listed below
Sorting:
- Fully and Partially Bayesian Neural Nets☆75Updated 4 months ago
- Spring 2023 seminar on automated experiment☆23Updated 2 years ago
- Gaussian process augmented with a probabilistic model of expected system's behavior☆15Updated 3 years ago
- A Bayesian optimization toolbox built on TensorFlow☆239Updated last week
- Fast Bayesian optimization, quadrature, inference over arbitrary domain with GPU parallel acceleration☆28Updated 3 weeks ago
- ☆40Updated last year
- Gaussian processes in JAX and Flax.☆529Updated this week
- Experimental design and (multi-objective) bayesian optimization.☆306Updated this week
- Materials for ACerS Automated Experiment Course☆20Updated last year
- Stochastic Gradient MCMC for Jax☆14Updated 3 months ago
- A software package for flexible HPC GPs☆16Updated last week
- Invariant representation learning from imaging and spectral data☆51Updated last year
- The materials for the Spring Mathematics in Materials course at the UTK MSE☆49Updated last year
- (NeurIPS 2022) Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination☆19Updated last year
- Matrix-free linear algebra in JAX.☆138Updated last week
- FoKL-GP implements Karhunen-Loève decomposed Gaussian processes with built-in forward variable selection. Decomposed GPs are key to embed…☆18Updated this week
- ☆26Updated 7 months ago
- Normalizing-flow enhanced sampling package for probabilistic inference in Jax☆248Updated last week
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆112Updated 5 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 10 months ago
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆90Updated 2 weeks ago
- ☆182Updated 2 weeks ago
- Interpolation and function approximation with JAX☆213Updated 2 weeks ago
- The tiniest of Gaussian Process libraries☆316Updated 3 weeks ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Probabilistic Numerics in Python.☆453Updated last month
- A system for scientific simulation-based inference at scale.☆164Updated last year
- kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order☆74Updated 8 months ago
- Python Library for Generalized Gaussian Process Modeling☆25Updated 5 months ago
- Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX☆207Updated 3 weeks ago