Alternatives and similar repositories for VariationalRNN

Users that are interested in VariationalRNN are comparing it to the libraries listed below

• probabilistic-learning / HI-VAE
  ☆91Updated 2 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆41Updated last year
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• emited / VariationalRecurrentNeuralNetwork
  Pytorch implementation of the Variational Recurrent Neural Network (VRNN).
  ☆285Updated 3 years ago
• sjblim / rmsn_nips_2018
  ☆39Updated 6 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated last year
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• simonkamronn / kvae
  Kalman Variational Auto-Encoder
  ☆136Updated 6 years ago
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 6 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆99Updated 5 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• tailintalent / causal
  Discovering directional relations via minimum predictive information regularization
  ☆24Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 4 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated 11 months ago
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆59Updated 5 months ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆35Updated 5 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆43Updated 6 years ago
• RuiShu / cvae
  Conditional variational autoencoder implementation in Torch
  ☆105Updated 9 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• msesia / chr
  Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
  ☆21Updated 3 years ago
• clinicalml / gumbel-max-scm
  Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)
  ☆43Updated 4 years ago
• prasoongoyal / bnp-vae
  ☆11Updated 7 years ago