anh-tong / signaxLinks
Signax: Signature computation in JAX
☆36Updated 8 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.☆55Updated last year
- Toolbox for working with streaming data as rough paths in Python☆40Updated this week
- Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)☆284Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated last year
- 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
- ☆154Updated 3 years ago
- esig python package☆48Updated 9 months ago
- ☆189Updated 2 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years 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
- A framework for composing Neural Processes in Python☆85Updated 9 months ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 11 months ago
- Gaussian processes in JAX and Flax.☆540Updated this week
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆452Updated last month
- Gaussian process modelling in Python☆224Updated 9 months ago
- State of the art inference for your bayesian models.☆222Updated 5 months ago
- Black-Box Inference foR Differentiable Simulators☆20Updated 11 months ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆226Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆70Updated 4 months ago
- Structural Time Series in JAX☆200Updated last year
- Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes☆49Updated 3 years ago
- Random Matrix Theory library - RMT analysis and simulation in Python☆51Updated last month
- Normalizing flows in PyTorch☆410Updated last week
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆233Updated 11 months ago