Alternatives and similar repositories for CausalTransformer

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

• IntelLabs / causality-lab
  Causal discovery algorithms and tools for implementing new ones
  ☆223Updated 3 weeks ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆216Updated 3 years ago
• CausalAILab / NeuralCausalModels
  Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.
  ☆24Updated 2 years ago
• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆123Updated last year
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆87Updated 3 months ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆84Updated last year
• microsoft / csuite
  CSuite: A Suite of Benchmark Datasets for Causality
  ☆72Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆66Updated 5 months ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆26Updated 3 months ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• Rose-STL-Lab / MCD
  Implementation of the ICML 2024 paper "Discovering Mixtures of Structural Causal Models from Time Series Data"
  ☆21Updated last month
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆100Updated 3 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆59Updated 5 months ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆77Updated 4 years ago
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆113Updated last month
• fishmoon1234 / DAG-NoCurl
  ☆25Updated 3 years ago
• TURuibo / Neuropathic-Pain-Diagnosis-Simulator
  Neuropathic Pain Diagnosis Simulator
  ☆11Updated 2 years ago
• xiangyu-sun-789 / NTS-NOTEARS
  Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  ☆27Updated 2 years ago
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆53Updated 5 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆60Updated 2 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆223Updated 4 years ago
• felixleopoldo / benchpress
  Scalable open-source software to run, develop, and benchmark causal discovery algorithms
  ☆71Updated last month
• hlzhang109 / TransTEE
  ☆35Updated 3 years ago