lahramon
Follow
Stars
Transforms your CasADi functions into batchable JAX-compatible functions. By combining the power of CasADi with the flexibility of JAX, JAXADi enables the creation of efficient code that runs smoot…
Tired of pushing to test your .gitlab-ci.yml?
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
Code for 'Transport with Support: Data-Conditional Diffusion Bridges'
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
Safe Exploration with MPC and Gaussian process models
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems
A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
A lightweight conic solver for second-order cone programming.
Basic linear algebra subroutines for embedded optimization
A dual-control effect preserving formulation for nonlinear output-feedback stochastic model predictive control with constraints
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Hardware accelerated, batchable and differentiable optimizers in JAX.
Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and custom information operators. Compatible with the broader JAX s…
Physics-Enhanced Regression for Initial Value Problems
Fenrir: Physics-Enhanced Regression for Initial Value Problems - Experiments
The Core Flight System (cFS) Operating System Abstraction Layer (OSAL)