mcusi / tf_dpgmmLinks
Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)
☆13Updated 7 years ago
Alternatives and similar repositories for tf_dpgmm
Users that are interested in tf_dpgmm are comparing it to the libraries listed below
Sorting:
- Python implementation of the PR-SSM.☆56Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆19Updated 3 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 8 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 3 years ago
- PyTorch implementation of the Covariate-GPLVM☆25Updated 5 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 3 years ago
- Code for "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis"☆27Updated 5 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆35Updated 11 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆101Updated 7 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated last year
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆45Updated 5 years ago
- Variational Dirichlet Process Gaussian Mixture Models☆29Updated 10 years ago
- ☆78Updated 4 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆46Updated 7 years ago
- Kalman Variational Auto-Encoder☆138Updated 6 years ago
- Gaussian Process Prior Variational Autoencoder☆87Updated 7 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Implementation of the Neural Clustering Process algorithm in Pytorch☆31Updated 5 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆43Updated 8 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- ☆14Updated 7 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆49Updated 8 months ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for AISTATS 2017 paper on "Conjugate-Computation Variational Inference"☆20Updated 5 years ago