Alternatives and similar repositories for Transformer-Hawkes-Process

Users that are interested in Transformer-Hawkes-Process are comparing it to the libraries listed below

• QiangAIResearcher / sahp_repo
  ☆62Updated 5 years ago
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆120Updated 7 months ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆88Updated 5 years ago
• xiao03 / nh
  A PyTorch Implementation of Neural Hawkes Process. Redefined.
  ☆35Updated 5 years ago
• woshiyyya / ERPP-RMTPP
  A pytorch implementation of ERPP and RMTPP on ATM maintenance dataset.
  ☆55Updated 6 years ago
• hongyuanmei / neurawkes
  Source code of The Neural Hawkes Process (NIPS 2017)
  ☆229Updated 4 years ago
• ant-research / EasyTemporalPointProcess
  EasyTPP: Towards Open Benchmarking Temporal Point Processes
  ☆331Updated 2 months ago
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆62Updated last year
• ajboyd2 / vae_mpp
  Variational Autoencoders for Marked Point Processes
  ☆15Updated 5 years ago
• HongtengXu / Hawkes-Process-Toolkit
  A toolbox of Hawkes processes
  ☆116Updated 7 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆138Updated 5 years ago
• chaoshangcs / GTS
  Discrete Graph Structure Learning for Forecasting Multiple Time Series, ICLR 2021.
  ☆180Updated 4 years ago
• musically-ut / tf_rmtpp
  Recurrent Marked Temporal Point Processes
  ☆56Updated 4 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆44Updated 6 years ago
• EDAPINENUT / EDTPP
  ☆16Updated 3 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆223Updated 3 years ago
• dunan / NeuralPointProcess
  ☆90Updated 3 years ago
• ZijieH / LG-ODE
  ☆33Updated 3 years ago
• fishmoon1234 / DAG-GNN
  ☆319Updated 4 years ago
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆64Updated 5 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆236Updated 4 years ago
• razhangwei / CAUSE
  ☆32Updated 3 years ago
• stmorse / hawkes
  Python class for generation and parameter estimation of multivariate Hawkes processes
  ☆175Updated 5 months ago
• Hongrui24 / RMTPP-pytorch
  ☆18Updated 5 years ago
• DeepGraphLearning / ContinuousGNN
  ☆47Updated 4 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• EDAPINENUT / GNTPP
  This is the official codebase of `Exploring Generative Neural Temporal Point Process' (Accepted by TMLR).
  ☆21Updated 2 years ago
• kurowasan / GraN-DAG
  ☆97Updated 2 years ago
• Hongrui24 / NeuralHawkesPytorch
  ☆25Updated 5 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆78Updated 4 years ago