Alternatives and similar repositories for VACA

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

• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 4 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆26Updated 3 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆29Updated 7 months ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆63Updated 3 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆88Updated last year
• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆16Updated last year
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆90Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆34Updated 4 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• tk-rusch / GraphCON
  GraphCON (ICML 2022)
  ☆59Updated 3 years ago
• kurowasan / GraN-DAG
  ☆97Updated 2 years ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆27Updated 3 years ago
• jliu / graph-normalizing-flows
  Code for Graph Normalizing Flows.
  ☆63Updated 6 years ago
• psanch21 / causal-flows
  ☆52Updated last year
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆49Updated 6 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• nickruggeri / CLAP-interpretable-predictions
  Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".
  ☆14Updated 3 years ago
• CausalAILab / NeuralCausalModels
  Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.
  ☆31Updated 2 years ago
• yannadani / vcn_pytorch
  Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"
  ☆17Updated 4 years ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆84Updated 2 years ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆26Updated 2 years ago
• calvin-zcx / ndcn
  Neural Dynamics on Complex Networks
  ☆55Updated 5 years ago
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆55Updated 5 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆105Updated 4 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆40Updated 3 years ago
• slachapelle / disentanglement_via_mechanism_sparsity
  ☆18Updated last year
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated last year