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
Sorting:
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 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
- PyTorch implementation of the Covariate-GPLVM☆26Updated 5 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆34Updated 11 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- ☆19Updated 3 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 5 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 9 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 10 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆46Updated 3 weeks ago
- Variational Dirichlet Process Gaussian Mixture Models☆29Updated 10 years ago
- ☆32Updated 6 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Direct Gibbs sampling for DPMM using python.☆16Updated 7 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- Tree-structured recurrent switching linear dynamical systems☆36Updated 4 years ago
- Implementation of a model to make VAE and GMM train from each other☆26Updated 3 years ago
- ☆11Updated 8 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 7 months ago
- Differentiable DAG Sampling (ICLR 2022)☆37Updated 2 years ago
- Code for "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis"☆26Updated 5 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- investigating use of variational auto encoders with multinomial latent variables for unsupervised data.☆24Updated 7 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 2 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago