Alternatives and similar repositories for SIN

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

• WeijiaZhang24 / TEDVAE
  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.
  ☆25Updated 2 years ago
• hlzhang109 / TransTEE
  ☆33Updated 2 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆75Updated 3 years ago
• qinjr / RIM
  code for RIM
  ☆22Updated 2 years ago
• pd90506 / AMCF
  Explainable recommendation via interpretable feature mapping
  ☆18Updated 5 years ago
• Osier-Yi / SITE
  ☆58Updated 3 years ago
• RyanWangZf / CVIB-Rec
  Official Implementation of Information Theoretic Counterfactual Learning from Missing Not At Random Feedback. NeurIPS 2020.
  ☆28Updated 4 years ago
• yaochenzhu / Deep-Deconf
  Official codes of paper "Deep causal reasoning for recommendations (Deep-Deconf)". (TIST'23)
  ☆26Updated 2 years ago
• DeepGraphLearning / SPN
  ☆29Updated 2 years ago
• hongyuanmei / nce-mpp
  Source code for Noise-Contrastive Estimation for Multivariate Point Processes (NeurIPS 2020).
  ☆15Updated 4 years ago
• StatsDLMathsRecomSys / Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System
  ☆22Updated 4 years ago
• aaronwtr / cfrnet-reproduction
  Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causa…
  ☆17Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• ignavierng / notears-tensorflow
  Reimplementation of NOTEARS in Tensorflow
  ☆33Updated 2 years ago
• paras2612 / CauseBox
  Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…
  ☆21Updated 3 years ago
• vveitch / causal-network-embeddings
  Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
  ☆56Updated 2 years ago
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 6 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.
  ☆30Updated 5 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆34Updated last year
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 4 years ago
• gizemt / CausalRecommendation
  Causal inference for recommendation
  ☆24Updated 6 years ago
• GentleZhu / EGI
  Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')
  ☆23Updated 3 years ago
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆36Updated 2 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated 10 months ago
• edebrouwer / cfqp
  Deep Counterfactual Prediction with Categorical Backward Variables
  ☆12Updated 2 years ago
• yixinwang / representation-causal-public
  ☆44Updated 3 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆25Updated last month
• caus-am / dom_adapt
  Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"
  ☆18Updated 4 years ago