alan-turing-institute / autoemulateLinks
Emulate simulations easily
☆106Updated this week
Alternatives and similar repositories for autoemulate
Users that are interested in autoemulate are comparing it to the libraries listed below
Sorting:
- Package for fitting Gaussian Process Emulators to multiple output computer simulation results.☆53Updated 2 years ago
- Python package 'dgpsi' for deep and linked Gaussian process emulations☆28Updated last month
- Literature and light wrappers for gaussian process models.☆47Updated 4 years ago
- A framework for composing Neural Processes in Python☆89Updated last year
- The tiniest of Gaussian Process libraries☆328Updated last week
- Interpolation and function approximation with JAX☆237Updated this week
- Gaussian processes with spherical harmonic features in JAX☆15Updated 4 months ago
- ☆25Updated this week
- python Parameter EStimation TOolbox☆265Updated 3 weeks ago
- Finite difference tools in JAX☆23Updated last year
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- A Bayesian optimization toolbox built on TensorFlow☆244Updated last week
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Gaussian processes in JAX and Flax.☆574Updated this week
- Bootcamp notebooks☆62Updated 5 months ago
- Methods for numerical differentiation of noisy data in python☆130Updated last month
- Universal, autodiff-native software components for Simulation Intelligence. 📦☆87Updated this week
- Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…☆84Updated 3 years ago
- Coordinate Axes for JAX☆59Updated last week
- Optimal numerical differentiation of noisy time series data in python.☆67Updated last month
- ☆68Updated 6 months ago
- Unleash the true power of scheduling☆33Updated 9 months ago
- Gaussian Processes for Experimental Sciences☆232Updated 6 months ago
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆94Updated 3 weeks ago
- Learning function operators with neural networks.☆35Updated last year
- Fully and Partially Bayesian Neural Nets☆80Updated 8 months ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- Learning Neural Differential Algebraic Equations via Operator Splitting☆21Updated 5 months ago
- ☆206Updated 2 months ago
- Probabilistic deep learning using JAX☆15Updated 11 months ago