Alternatives and similar repositories for cdml-neurips2020

Users that are interested in cdml-neurips2020 are comparing it to the libraries listed below

• sweichwald / tidybench
  TIme series DiscoverY BENCHmark (tidybench)
  ☆38Updated last year
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆53Updated 5 years ago
• sakhanna / SRU_for_GCI
  Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality
  ☆36Updated 5 years ago
• ioanabica / Time-Series-Deconfounder
  Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …
  ☆52Updated 4 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆229Updated 4 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆217Updated 3 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆54Updated 4 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆79Updated 4 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• xiangyu-sun-789 / NTS-NOTEARS
  Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  ☆27Updated 2 years ago
• kuiy / CausalFS
  An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)
  ☆62Updated 4 years ago
• felixleopoldo / benchpress
  Scalable open-source software to run, develop, and benchmark causal discovery algorithms
  ☆72Updated this week
• amber0309 / ANM-MM
  Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"
  ☆23Updated 6 years ago
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆93Updated 6 months ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆46Updated 3 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆68Updated 8 months ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆26Updated 3 years ago
• kurowasan / GraN-DAG
  ☆97Updated 2 years ago
• sanatonek / time_series_explainability
  ☆62Updated 4 years ago
• wt-hu / pyCausalFS
  pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification
  ☆70Updated 4 years ago
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆62Updated last year
• cmu-phil / py-tetrad
  Makes algorithms/code in Tetrad available in Python via JPype
  ☆87Updated 2 weeks ago
• py-why / dodiscover
  [Experimental] Global causal discovery algorithms
  ☆109Updated last week
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆50Updated 6 years ago
• yromano / cqr
  Conformalized Quantile Regression
  ☆288Updated 3 years ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆100Updated 3 years ago
• M-Nauta / TCDF
  Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
  ☆523Updated 4 years ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆142Updated 2 years ago
• vanderschaarlab / MIRACLE
  ☆29Updated last year