Alternatives and similar repositories for CAUSE

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

• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆86Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 3 years ago
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆61Updated 8 months ago
• vveitch / causal-network-embeddings
  Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
  ☆57Updated 2 years ago
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆62Updated 4 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆43Updated 6 years ago
• yangalan123 / TemporalPointProcessPapers
  Paper lists for Temporal Point Process
  ☆113Updated 2 months ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• StatsDLMathsRecomSys / Self-attention-with-Functional-Time-Representation-Learning
  ☆49Updated 2 years ago
• SimiaoZuo / Transformer-Hawkes-Process
  Code for Transformer Hawkes Process, ICML 2020.
  ☆198Updated last year
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆75Updated 4 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
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆133Updated 5 years ago
• dunan / NeuralPointProcess
  ☆89Updated 2 years ago
• hongyuanmei / neurawkes
  Source code of The Neural Hawkes Process (NIPS 2017)
  ☆225Updated 3 years ago
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆61Updated last year
• ajboyd2 / vae_mpp
  Variational Autoencoders for Marked Point Processes
  ☆15Updated 5 years ago
• musically-ut / tf_rmtpp
  Recurrent Marked Temporal Point Processes
  ☆56Updated 4 years ago
• geopanag / pandemic_tgnn
  ☆47Updated 10 months ago
• kurowasan / GraN-DAG
  ☆96Updated 2 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆218Updated 3 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• xiao03 / nh
  A PyTorch Implementation of Neural Hawkes Process. Redefined.
  ☆34Updated 5 years ago
• jma712 / HyperSCI
  ☆46Updated last year
• EDAPINENUT / GNTPP
  This is the official codebase of `Exploring Generative Neural Temporal Point Process' (Accepted by TMLR).
  ☆20Updated 2 years ago
• uoguelph-mlrg / LDG
  PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"
  ☆101Updated 4 years ago
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated last year
• woshiyyya / ERPP-RMTPP
  A pytorch implementation of ERPP and RMTPP on ATM maintenance dataset.
  ☆54Updated 6 years ago
• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆43Updated 3 years ago
• HongtengXu / Hawkes-Process-Toolkit
  A toolbox of Hawkes processes
  ☆115Updated 7 years ago