BorealisAI / continuous-time-flow-processLinks
PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
☆48Updated 4 years ago
Alternatives and similar repositories for continuous-time-flow-process
Users that are interested in continuous-time-flow-process are comparing it to the libraries listed below
Sorting:
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆59Updated 4 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated 2 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- Experiments for Neural Flows paper☆95Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 5 years ago
- ☆15Updated 3 months ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- ☆23Updated 3 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆32Updated 3 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 8 months ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Sequential Neural Likelihood☆40Updated 5 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆128Updated 9 months ago
- Example applications of path signatures☆39Updated 2 months ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Signax: Signature computation in JAX☆29Updated 4 months ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 10 months ago
- PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…☆25Updated last year
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆22Updated 6 years ago
- Pytorch implementation of RED-SDS (NeurIPS 2021).☆18Updated 3 years ago
- Code for our paper: Online Variational Filtering and Parameter Learning☆18Updated 3 years ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- PyTorch implementation of the Masked Autoregressive Flow☆27Updated 4 years ago