Alternatives and similar repositories for grm:

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

• gbrltv / business_process_encoding
  Business Process Encoding
  ☆12Updated 8 months ago
• annguy / time-aware-pbpm
  ☆13Updated 3 years ago
• farbodtaymouri / GanPredictiveMonitoring
  ☆20Updated 3 years ago
• irhete / predictive-monitoring-benchmark
  Comparative experimental evaluation of outcome-oriented predictive monitoring techniques on a benchmark consisting of 24 real-world datas…
  ☆32Updated 3 years ago
• Zaharah / processtransformer
  Transformer Network for Predictive Business Process Monitoring Tasks
  ☆40Updated 6 months ago
• zahradbozorgi / CausalRulesDiscovery
  https://arxiv.org/abs/2009.01561
  ☆23Updated 2 years ago
• zahradbozorgi / prescriptiveMonitoringORF
  ☆11Updated 3 years ago
• grandintegrator / Link-Prediction-Supply-Chains
  MPhil thesis code for link prediction in supply chains
  ☆18Updated 2 years ago
• chaoshangcs / GTS
  Discrete Graph Structure Learning for Forecasting Multiple Time Series, ICLR 2021.
  ☆172Updated 3 years ago
• Graph-Machine-Learning-Group / sgp
  Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)
  ☆46Updated last year
• StatsDLMathsRecomSys / Inductive-representation-learning-on-temporal-graphs
  ☆311Updated 8 months ago
• francxx96 / declare4py
  A Python package for process-mining with DECLARE models.
  ☆15Updated 9 months 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)
  ☆163Updated 2 years ago
• spindro / GINN
  Graph Imputation Neural Network
  ☆78Updated 5 years ago
• huytjuh / Subsequence-Time-Series-Clustering
  Extending state-of-the-art Time Series Forecasting with Subsequence Time Series (STS) Clustering to enforce model seasonality adaptation.
  ☆16Updated 2 years ago
• StephenPauwels / edbn
  Repository containing all implementations and experiments for the EDBN model.
  ☆18Updated 3 years ago
• wondergo2017 / DHGAS
  Implementation codes for AAAI23 paper "Dynamic Heterogeneous Graph Attention Neural Architecture Search"
  ☆27Updated last year
• zxj32 / GCN-GRU
  Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data
  ☆28Updated 5 years ago
• radrumond / timehetnet
  Learning complex time series forecasting models usually requires a large amount of data, as each model is trained from scratch for each t…
  ☆42Updated 2 years ago
• saimunikoti / GraphNeuralNetwork-Resilience-ComplexNetworks
  ☆12Updated 2 years ago
• kyawlin / GNN-finance
  Curated list of Graph Neural Network Applications in Business, Finance and Banking
  ☆85Updated 8 months ago
• SelfExplainML / GamiNet-PyTorch
  ☆12Updated last year
• odinhg / Graph-Neural-Networks-INF367A
  Traffic prediction with graph neural network using PyTorch Geometric. The implementation uses the MetaLayer class to build the GNN which …
  ☆24Updated last year
• peaclab / CoMTE
  Counterfactual Explanations for Multivariate Time Series Data
  ☆31Updated last year
• BrechtWts / SuffixTransformerNetwork
  ☆11Updated 7 months ago
• giovanniMen / CPCaD-Bench
  Continuous Industrial Process datasets for benchmarking Causal Discovery methods
  ☆27Updated 2 years ago
• mangushev / mtad-gat
  Implementation of MTAD-GAT: Multivariate Time-series Anomaly Detection via Graph Attention Network
  ☆95Updated 3 years ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆96Updated 3 years ago
• timbrockmeyer / pytorch-geometric-temporal-examples
  Short examples using the PyTorch Geometric Temporal library for temporal Graph Neural Networks (GNN).
  ☆17Updated 3 years ago
• TrustAGI-Lab / MTGODE
  [TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".
  ☆81Updated 2 years ago