yiyuezhuo / Deep-Latent-Gaussian-Models
PyTorch implementation for Deep Latent Gaussian Models(DLGM) https://arxiv.org/abs/1401.4082
☆9Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for Deep-Latent-Gaussian-Models
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 5 years ago
- Clean repo for tensor-train RNN implemented in TensorFlow☆68Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 4 years ago
- Time-varying Autoregression with Low Rank Tensors☆15Updated 3 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 6 years ago
- Hierarchical Change-Point Detection☆13Updated 6 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Pyro/Pytorch implementation of Deep Kalman FIlter for shared-mobility demand prediction☆42Updated 4 years ago
- ☆19Updated last year
- Riemannian stochastic optimization algorithms: Version 1.0.3☆63Updated last year
- This is all the codes used in "Large Scale Online Kernel Learning"☆11Updated 7 years ago
- TensorFlow Probability Tutorial☆36Updated 5 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 8 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Modeling Uncertainty in RNNs for Time Series Forecasting☆14Updated 6 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Generative Adversarial Networks for time-series generation☆9Updated 5 years ago
- Dirichlet Process Mixture Models☆22Updated 8 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 7 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 4 years ago
- An encoder-decoder framework for learning from incomplete data☆45Updated last year
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 2 years ago
- ☆28Updated 5 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated last year
- State-space deep Gaussian processes in Python and Matlab☆29Updated 2 years ago
- Tensorflow 2.x implementation of the beta-TCVAE (arXiv:1802.04942).☆15Updated 5 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago