datang1992 / Correlated-VAEsLinks
Code for my ICML 2019 paper "Correlated Variational Auto-Encoders"
☆15Updated 6 years ago
Alternatives and similar repositories for Correlated-VAEs
Users that are interested in Correlated-VAEs are comparing it to the libraries listed below
Sorting:
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Updated 8 years ago
- code release for the NIPS 2016 paper☆27Updated 8 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 11 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- A Python implementation of Kernel Mean Matching data reweighting algorithm☆33Updated 9 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Code for Graphite iterative graph generation☆59Updated 6 years ago
- ☆91Updated 6 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 6 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Tensorflow implementation of Hyperspherical Variational Auto-Encoders☆233Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- STCN: Stochastic Temporal Convolutional Networks☆69Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- Black Box Variational Inference for Bayesian logistic regression☆18Updated 8 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆102Updated 6 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 8 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago