simonkamronn / kvaeLinks
Kalman Variational Auto-Encoder
☆137Updated 6 years ago
Alternatives and similar repositories for kvae
Users that are interested in kvae are comparing it to the libraries listed below
Sorting:
- Structured Inference Networks for Nonlinear State Space Models☆275Updated 8 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆355Updated 8 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 8 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆45Updated 7 years ago
- Python implementation of the PR-SSM.☆56Updated 7 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- ☆110Updated 8 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆94Updated 7 years ago
- ☆14Updated 7 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Mixture Density Networks (MDN) implemented in PyTorch☆65Updated 5 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- Deep Markov Models☆132Updated 6 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- PyTorch implementation of Neural Processes☆88Updated 6 years ago
- Pytorch implementation of Block Neural Autoregressive Flow☆181Updated 4 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- Deep convolutional gaussian processes.☆81Updated 6 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago