anh-tong / signaxLinks
Signax: Signature computation in JAX
☆35Updated 7 months ago
Alternatives and similar repositories for signax
Users that are interested in signax are comparing it to the libraries listed below
Sorting:
- Differentiable computations for the signature-PDE-kernel on CPU and GPU.☆56Updated last year
- Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)☆283Updated last year
- Toolbox for working with streaming data as rough paths in Python☆40Updated this week
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆48Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated last year
- esig python package☆48Updated 9 months ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆237Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆62Updated 4 years ago
- ☆153Updated 3 years ago
- ☆187Updated last month
- A framework for composing Neural Processes in Python☆85Updated 9 months ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- Simple (and cheap!) neural network uncertainty estimation☆69Updated 3 months ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆61Updated last year
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 11 months ago
- IVON optimizer for neural networks based on variational learning.☆72Updated 10 months ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Gaussian processes in JAX and Flax.☆537Updated this week
- Code for "Deep Signature Transforms" (NeurIPS 2019)☆97Updated last year
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆232Updated 10 months ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆448Updated 2 weeks ago
- State of the art inference for your bayesian models.☆222Updated 4 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Kernel Identification Through Transformers☆14Updated 2 years ago