Alternatives and similar repositories for NeuralCausalModels:

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

• CausalAILab / NCMCounterfactuals
  ☆12Updated 2 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 3 years ago
• xiangyu-sun-789 / NTS-NOTEARS
  Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  ☆23Updated 2 years ago
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆53Updated 4 years ago
• kurowasan / GraN-DAG
  ☆92Updated 2 years ago
• IntelLabs / causality-lab
  Causal discovery algorithms and tools for implementing new ones
  ☆217Updated 2 months ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆96Updated 3 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆82Updated last year
• Valentyn1997 / CausalTransformer
  Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"
  ☆146Updated 7 months ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆50Updated 6 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆24Updated last year
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆73Updated 3 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆63Updated last month
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆81Updated last year
• lmz123321 / proxy_causal_discovery
  Official implementation for NeurIPS23 paper: Causal Discovery from Subsampled Time Series with Proxy Variable
  ☆28Updated 10 months ago
• sjblim / rmsn_nips_2018
  ☆37Updated 6 years ago
• causalens / cdml-neurips2020
  This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…
  ☆59Updated 7 months ago
• fishmoon1234 / DAG-NoCurl
  ☆25Updated 3 years ago
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆56Updated last month
• sakhanna / SRU_for_GCI
  Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality
  ☆34Updated 4 years ago
• microsoft / csuite
  CSuite: A Suite of Benchmark Datasets for Causality
  ☆67Updated last year
• ignavierng / notears-tensorflow
  Reimplementation of NOTEARS in Tensorflow
  ☆35Updated 2 years ago
• songjiang0909 / Causal-Inference-on-Networked-Data
  Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"
  ☆15Updated 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…
  ☆115Updated last year
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆111Updated 5 months ago
• WeijiaZhang24 / TEDVAE
  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.
  ☆24Updated 2 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆72Updated 4 years ago