razhangwei / CAUSE
☆30Updated 3 years ago
Alternatives and similar repositories for CAUSE:
Users that are interested in CAUSE are comparing it to the libraries listed below
- Source code of the neural Hawkes particle smoothing (ICML 2019)☆43Updated 5 years ago
- Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)☆84Updated 4 years ago
- Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)☆23Updated last year
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 2 years ago
- This is the official codebase of `Exploring Generative Neural Temporal Point Process' (Accepted by TMLR).☆19Updated last year
- A PyTorch Implementation of Neural Hawkes Process. Redefined.☆32Updated 4 years ago
- ☆50Updated last year
- Recurrent Marked Temporal Point Processes☆56Updated 3 years ago
- Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)☆57Updated 2 months ago
- ☆22Updated 2 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆56Updated 2 years ago
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 2 years ago
- Variational Autoencoders for Marked Point Processes☆15Updated 4 years ago
- code for "Fully Neural Network based Model for General Temporal Point Processes"☆60Updated 4 years ago
- Discovering directional relations via minimum predictive information regularization☆23Updated 5 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆74Updated 3 years ago
- ☆29Updated last year
- 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
- ☆14Updated 3 years ago
- A short course on temporal point process and modeling irregular time series☆21Updated 4 years ago
- ☆59Updated 4 years ago
- ☆89Updated 2 years ago
- ☆15Updated 4 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆35Updated 2 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆30Updated 5 years ago
- ☆20Updated 3 years ago
- This repository contains recent background materials, current works, and codes for researching in TPP.☆16Updated last year
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆58Updated 11 months ago