Alternatives and similar repositories for proxy_causal_discovery

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

• jarrycyx / UNN
  Causal Neural Nerwork
  ☆142Updated 2 months ago
• sakhanna / SRU_for_GCI
  Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality
  ☆35Updated 5 years ago
• i6092467 / GVAR
  An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
  ☆79Updated 2 years ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆103Updated 3 years ago
• JonathanCrabbe / Dynamask
  This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…
  ☆75Updated 3 years ago
• CausalRivers / causalrivers
  The CausalRivers benchmark package. Evaluate your Causal Discovery method on real-world data.
  ☆37Updated 3 months ago
• DMIRLAB-Group / SASA
  ☆44Updated 2 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆229Updated 4 years ago
• mims-harvard / Raindrop
  Graph Neural Networks for Irregular Time Series
  ☆214Updated 3 years ago
• zhycs / LaST
  Code for paper titled "Learning Latent Seasonal-Trend Representations for Time Series Forecasting" in NeurIPS 2022
  ☆82Updated 3 years ago
• lingbai-kong / CausalFormer
  PyTorch Implementation of CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
  ☆73Updated 7 months ago
• xiangyu-sun-789 / NTS-NOTEARS
  Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  ☆27Updated 2 years ago
• reml-lab / mTAN
  Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
  ☆138Updated 4 years ago
• Graph-Machine-Learning-Group / grin
  Official repository for the paper "Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks" (ICLR 2022)
  ☆173Updated 3 years ago
• Z-GCNETs / Z-GCNETs
  ☆42Updated 4 years ago
• Graph-Machine-Learning-Group / sgp
  Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)
  ☆50Updated 2 years ago
• TrustAGI-Lab / MTGODE
  [TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".
  ☆88Updated 3 years ago
• EternityZY / STNSCM
  This is the official release code of AAAI2023 accepted paper: "Spatial temporal Neural Structural Causal Models for Bike Flow Prediction"
  ☆41Updated 2 years ago
• weifantt / DEPTS
  ☆42Updated 3 years ago
• pfnet-research / TabCSDI
  A code for the NeurIPS 2022 Table Representation Learning Workshop paper: "Diffusion models for missing value imputation in tabular data"
  ☆56Updated last year
• gabrielspadon / ReGENN
  Recurrent Graph Evolution Neural Network (ReGENN) using Graph Soft Evolution (GSE)
  ☆30Updated last year
• Leezekun / ViTST
  [NeurIPS 2023] The official repo for the paper: "Time Series as Images: Vision Transformer for Irregularly Sampled Time Series"."
  ☆159Updated 2 years ago
• chaoshangcs / GTS
  Discrete Graph Structure Learning for Forecasting Multiple Time Series, ICLR 2021.
  ☆178Updated 4 years ago
• wt-hu / pyCausalFS
  pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification
  ☆71Updated 5 years ago
• AdityaLab / EpiFNP
  Official repo to paper
  ☆13Updated 2 years ago
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 4 years ago
• hongmingli1995 / CR-VAE
  ☆32Updated 2 years ago
• alipay / RGSL
  ☆44Updated 3 years ago
• giovanniMen / CPCaD-Bench
  Continuous Industrial Process datasets for benchmarking Causal Discovery methods
  ☆34Updated 3 years ago
• cruiseresearchgroup / TSCP2
  Time Series Change Point Detection based on Contrastive Predictive Coding
  ☆84Updated 3 years ago