crazysal / VariationalRNN
A Recurrent Latent Variable Model for Sequential Data
☆24Updated 6 years ago
Alternatives and similar repositories for VariationalRNN:
Users that are interested in VariationalRNN are comparing it to the libraries listed below
- ☆90Updated 2 years ago
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]☆56Updated 8 months ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- State space modeling with recurrent neural networks☆43Updated 6 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆37Updated last year
- ☆37Updated 6 years ago
- Pytorch implementation of the Variational Recurrent Neural Network (VRNN).☆285Updated 3 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- pytorch (>=0.4 version) code of NIPS 2015 paper 'A Recurrent Latent Variable Model for Sequential Data'☆13Updated 5 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆33Updated 11 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago
- Discovering directional relations via minimum predictive information regularization☆23Updated 5 years ago
- CEVAE with VampPrior☆11Updated 6 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- Kalman Variational Auto-Encoder☆135Updated 6 years ago
- An encoder-decoder framework for learning from incomplete data☆46Updated last year
- Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf☆21Updated 5 years ago
- Conditional variational autoencoder implementation in Torch☆105Updated 9 years ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated 2 years ago
- 🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…☆41Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Modeling the asynchronous event sequence via Recurrent Point Process☆61Updated 7 years ago
- PPG (Point Process Generator) is a Reinforcement Learning framework that is able to produce actions by imitating expert sequences.☆13Updated 5 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆99Updated 5 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆42Updated 7 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆42Updated 4 years ago