NikitaChizhov / deep_kalman_filter_for_BM
☆14Updated 6 years ago
Alternatives and similar repositories for deep_kalman_filter_for_BM:
Users that are interested in deep_kalman_filter_for_BM are comparing it to the libraries listed below
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- TensorFlow impementation of: Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images☆65Updated 8 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆81Updated 4 years ago
- Various estimators of the infinite dimensional exponential family model☆15Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Lagrangian VAE☆28Updated 6 years ago
- ☆47Updated 2 years ago
- Tree-structured recurrent switching linear dynamical systems☆36Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- Implementation of Deep Variational Bayes Filter☆12Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 3 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- ☆28Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- PyTorch implementation of AVF☆45Updated 4 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago