Alternatives and similar repositories for DiffAN

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

• patrickrchao / DiffusionBasedCausalModels
  ☆26Updated 3 months ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆84Updated last year
• psanch21 / causal-flows
  ☆51Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆66Updated 5 months ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆60Updated 2 years ago
• vios-s / Diff-SCM
  Code for Diff-SCM paper
  ☆97Updated 2 years ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆55Updated last year
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• juangamella / aicp
  Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…
  ☆21Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years 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
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 2 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆102Updated 4 years ago
• namkoong-lab / whyshift
  A python package providing a benchmark with various specified distribution shift patterns.
  ☆58Updated last year
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆37Updated 5 years ago
• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆67Updated 2 years ago
• psanch21 / VACA
  ☆23Updated 3 years ago
• paulrolland1307 / SCORE
  Code used in the paper "Score matching enables causal discovery of nonlinear additive noise models", Rolland et al., ICML 2022
  ☆19Updated 3 years ago
• ifiaposto / Distance_Aware_Bottleneck
  Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024
  ☆28Updated 11 months ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 3 years ago
• CausalAILab / NCMCounterfactuals
  ☆12Updated 2 years ago
• Valentyn1997 / CausalTransformer
  Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"
  ☆153Updated 11 months ago
• sharpenb / Differentiable-DAG-Sampling
  Differentiable DAG Sampling (ICLR 2022)
  ☆37Updated 3 years ago
• yannadani / vcn_pytorch
  Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"
  ☆17Updated 3 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆68Updated 8 months ago