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.☆60Updated 4 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated 2 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆32Updated 3 years ago
- Refining continuous-in-depth neural networks☆40Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 5 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- PyTorch implementation of the Masked Autoregressive Flow☆28Updated 4 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 10 months ago
- Differentiable computations for the signature-PDE-kernel on CPU and GPU.☆55Updated last year
- ☆24Updated 3 years ago
- ☆15Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 8 months ago
- Kernel Identification Through Transformers☆12Updated 2 years ago
- Official implementation of Transformer Neural Processes☆78Updated 2 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch☆22Updated 5 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago