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
  ☆37Updated 5 years 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"
  ☆89Updated 3 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• akekic / causal-component-analysis
  ☆25Updated last year
• nmichlo / disent
  🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervi…
  ☆128Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• psanch21 / causal-flows
  ☆51Updated last year
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆84Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆65Updated 6 months ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆55Updated last year
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆227Updated 10 months ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆69Updated 3 months ago
• gemoran / sparse-vae-code
  ☆32Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆74Updated 3 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆47Updated 6 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 months ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆34Updated 4 months ago
• dimkal89 / rvae
  ☆38Updated 5 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆127Updated last year
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆84Updated 6 years ago
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆51Updated last year
• iffsid / DReG-PyTorch
  A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"
  ☆18Updated 5 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago