kuleshov / neural-variational-inference
Neural variational inference and learning in undirected graphical models http://www.stanford.edu/~kuleshov/papers/nips2017.pdf
☆17Updated 6 years ago
Alternatives and similar repositories for neural-variational-inference:
Users that are interested in neural-variational-inference are comparing it to the libraries listed below
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 5 months ago
- General Latent Feature Modeling for Heterogeneous data☆48Updated last year
- ☆11Updated 7 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆43Updated 7 years ago
- implementation of different Dirichlet Variational Autoencoder Topic Models in Tensorflow☆49Updated 2 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- Black Box Variational Inference for Bayesian logistic regression☆18Updated 8 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 11 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆68Updated 10 years ago
- Learning Tree structures and Tree metrics☆23Updated 7 months ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Reweighted Expectation Maximization☆29Updated 5 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- CEVAE with VampPrior☆11Updated 6 years ago
- Mixed Membership Stochastic Blockmodel Implementation with 3 Inference Schemes☆24Updated 9 years ago
- Sequential Neural Likelihood☆39Updated 5 years ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆17Updated 3 years ago
- Structure learning for sparse graphs with latent variables☆45Updated 8 years ago
- ☆11Updated 8 years ago
- Deep Generative Models with Stick-Breaking Priors☆95Updated 8 years ago
- ☆153Updated 7 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 5 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆30Updated 4 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆14Updated 5 years ago