Alternatives and similar repositories for dyn-gfn

Users that are interested in dyn-gfn are comparing it to the libraries listed below

• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆74Updated 3 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆82Updated last year
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆87Updated 3 years ago
• psanch21 / causal-flows
  ☆51Updated 9 months ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆62Updated 3 months ago
• Genentech / dcdfg
  ☆24Updated 2 years ago
• yannadani / vcn_pytorch
  Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"
  ☆17Updated 3 years ago
• slachapelle / disentanglement_via_mechanism_sparsity
  ☆17Updated last year
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 3 years ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆22Updated 3 years ago
• sharpenb / Differentiable-DAG-Sampling
  Differentiable DAG Sampling (ICLR 2022)
  ☆37Updated 2 years ago
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆49Updated last year
• causalbench / causalbench
  ☆40Updated 6 months ago
• Qualcomm-AI-research / weakly-supervised-causal-representation-learning
  ☆29Updated last year
• larslorch / stadion
  Causal Modeling with Stationary Diffusions, AISTATS 2024
  ☆18Updated 2 months ago
• patrickrchao / DiffusionBasedCausalModels
  ☆25Updated 3 weeks ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• azizilab / sdcd
  Stable Differentiable Causal Discovery (SDCD)
  ☆22Updated 10 months ago
• akekic / causal-component-analysis
  ☆25Updated last year
• CausalAILab / NeuralCausalModels
  Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.
  ☆24Updated 2 years ago
• juangamella / aicp
  Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…
  ☆20Updated last year
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆35Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• rpatrik96 / ima-vae
  This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivale…
  ☆23Updated last year
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆117Updated last year