mcusi / tf_dpgmm
Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)
☆13Updated 6 years ago
Alternatives and similar repositories for tf_dpgmm:
Users that are interested in tf_dpgmm are comparing it to the libraries listed below
- ☆19Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago
- Code for "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis"☆26Updated 4 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 11 months ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆33Updated 11 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆17Updated 2 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆16Updated 3 years ago
- Tensorflow implementation for the SVGP-VAE model.☆21Updated 3 years ago
- Dirichlet Process Mixture Models☆22Updated 8 years ago
- Source code for "When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian …☆10Updated 3 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆37Updated 10 months ago
- Variational Dirichlet Process Gaussian Mixture Models☆27Updated 9 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆43Updated 3 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 3 years ago
- Variational Autoencoders & Normalizing Flows Project☆19Updated 8 years ago
- PyTorch implementation of the Covariate-GPLVM☆26Updated 4 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Direct Gibbs sampling for DPMM using python.☆16Updated 7 years ago