Alternatives and similar repositories for disentanglement_via_mechanism_sparsity

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

• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆24Updated 2 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆36Updated 5 years ago
• psanch21 / causal-flows
  ☆51Updated 11 months ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• nmichlo / disent
  🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervi…
  ☆127Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• gemoran / sparse-vae-code
  ☆32Updated 2 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆47Updated 6 years ago
• akekic / causal-component-analysis
  ☆25Updated last year
• is0383kk / Pytorch_VAE-GMM
  Implementation of a model to make VAE and GMM train from each other
  ☆26Updated 3 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆84Updated last year
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆126Updated last year
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆50Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆66Updated 5 months ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆55Updated last year
• sharpenb / Differentiable-DAG-Sampling
  Differentiable DAG Sampling (ICLR 2022)
  ☆37Updated 3 years ago
• Qualcomm-AI-research / weakly-supervised-causal-representation-learning
  ☆30Updated last year
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆32Updated 2 months ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆112Updated 3 years ago
• iffsid / mmvae
  Multimodal Mixture-of-Experts VAE
  ☆212Updated 2 years ago
• addtt / ladder-vae-pytorch
  Ladder Variational Autoencoders (LVAE) in PyTorch
  ☆91Updated 4 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• dimkal89 / rvae
  ☆38Updated 5 years ago