Alternatives and similar repositories for DAG-GNN

Users that are interested in DAG-GNN are comparing it to the libraries listed below

• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆216Updated 3 years ago
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆635Updated last year
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• keiichishima / pcalg
  CPDAG Estimation using PC-Algorithm
  ☆96Updated 3 years ago
• xiangyu-sun-789 / NTS-NOTEARS
  Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  ☆27Updated 2 years ago
• AMLab-Amsterdam / CEVAE
  Causal Effect Inference with Deep Latent-Variable Models
  ☆344Updated 5 years ago
• fishmoon1234 / DAG-NoCurl
  ☆25Updated 3 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆197Updated 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…
  ☆120Updated last year
• bd2kccd / py-causal
  ☆204Updated 2 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆75Updated 4 years ago
• uoguelph-mlrg / LDG
  PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"
  ☆103Updated 4 years ago
• huawei-noah / BGCN
  A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
  ☆161Updated 5 years ago
• d909b / perfect_match
  ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
  ☆129Updated 2 years ago
• ElementAI / causal_discovery_toolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆31Updated 5 years ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆61Updated 5 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• woshiyyya / ERPP-RMTPP
  A pytorch implementation of ERPP and RMTPP on ATM maintenance dataset.
  ☆55Updated 6 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆100Updated 6 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆132Updated 4 years ago
• CausalAILab / NeuralCausalModels
  Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.
  ☆24Updated 2 years ago
• SimiaoZuo / Transformer-Hawkes-Process
  Code for Transformer Hawkes Process, ICML 2020.
  ☆195Updated last year
• hongyuanmei / neurawkes
  Source code of The Neural Hawkes Process (NIPS 2017)
  ☆224Updated 3 years ago
• sharpenb / Differentiable-DAG-Sampling
  Differentiable DAG Sampling (ICLR 2022)
  ☆37Updated 3 years ago
• Biwei-Huang / Generalized-Score-Functions-for-Causal-Discovery
  A generalized score-based method for Causal Discovery
  ☆17Updated 4 years ago
• octeufer / Adversarial-Balancing-based-representation-learning-for-Causal-Effect-Inference
  Causal Inference
  ☆10Updated 5 years ago