Alternatives and similar repositories for SVAE-Revisited

Users that are interested in SVAE-Revisited are comparing it to the libraries listed below

• tachukao / mgplvm-pytorch
  ☆24Updated 2 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆37Updated 5 years ago
• lindermanlab / ssm-jax
  Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend
  ☆61Updated last year
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 5 years ago
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 2 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆38Updated 5 years ago
• HHalva / hmnlica
  Code for Hidden Markov Nonlinear ICA
  ☆24Updated 4 years ago
• vruetten / GPFADS
  Gaussian Process Factor Analysis with Dynamical Structure
  ☆17Updated 5 years ago
• slinderman / recurrent-slds
  Recurrent Switching Linear Dynamical Systems
  ☆113Updated 2 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• hmorioka / TCL
  Time-Contrastive Learning
  ☆66Updated 7 years ago
• mattjj / pyslds
  ☆98Updated 7 years ago
• iffsid / DReG-PyTorch
  A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"
  ☆18Updated 6 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆55Updated last year
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated last year
• dieterichlawson / snax
  ☆12Updated 2 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• jimmysmith1919 / JSLDS_public
  ☆12Updated 4 years ago
• lindermanlab / gpslds
  Project repo for gpSLDS
  ☆14Updated 10 months ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 7 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• is0383kk / Dirichlet-VAE
  Dirichlet-Variational Auto-Encoder by PyTorch
  ☆23Updated last month
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• BouchardLab / DynamicalComponentsAnalysis
  Dynamical Components Analysis
  ☆33Updated 2 months ago
• wiskott-lab / sklearn-sfa
  This project provides Slow Feature Analysis as a scikit-learn-style package.
  ☆41Updated 2 years ago