Alternatives and similar repositories for MCFlow

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

• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆63Updated 3 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆49Updated 6 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆105Updated 4 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆41Updated last year
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆33Updated 4 years ago
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 3 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 5 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆19Updated 4 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• probabilistic-learning / HI-VAE
  ☆91Updated 2 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆29Updated 7 months ago
• chl8856 / SEFS
  Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates
  ☆24Updated 2 years ago
• zxj32 / uncertainty-GNN
  Uncertainty Aware Semi-Supervised Learning on Graph Data
  ☆39Updated 4 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆90Updated 2 years ago
• psanch21 / VACA
  ☆24Updated 3 years ago
• boschresearch / GMM_DAE
  ☆20Updated 4 years ago
• volagold / nce
  Noise Contrastive Estimation (NCE) in PyTorch
  ☆32Updated 9 months ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆40Updated 3 years ago
• mori97 / VaDE
  A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)
  ☆39Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆26Updated 3 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 4 years ago
• dcmoyer / invariance-tutorial
  A tutorial on learned non-adversarial invariance in neural networks
  ☆13Updated 6 years ago
• abidlabs / contrastive_vae
  Contrastive Variational Autoencoders
  ☆71Updated 6 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• pfnet-research / TabCSDI
  A code for the NeurIPS 2022 Table Representation Learning Workshop paper: "Diffusion models for missing value imputation in tabular data"
  ☆56Updated last year
• zengyi-li / NMCE-release
  Code for Neural Manifold Clustering and Embedding
  ☆61Updated 3 years ago