Module for statistical learning, with a particular emphasis on time-dependent modelling
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Updated
Nov 27, 2024 - Python
Module for statistical learning, with a particular emphasis on time-dependent modelling
Umbrella package of the 'spatstat' family................
Spatiotemporal epidemic model introduced in the context of COVID-19, ACM TSAS, 2022
Pieces of code that have appeared on my blog.
A Spatio-temporal point process simulator.
A general framework for learning spatio-temporal point processes via reinforcement learning
A package for temporal point process modeling, simulation and inference
Code for "Long Horizon Forecasting With Temporal Point Processes", WSDM 2021
Code and real data for "Counterfactual Temporal Point Processes", NeurIPS 2022
PPG (Point Process Generator) is a Reinforcement Learning framework that is able to produce actions by imitating expert sequences.
A method for event correlation detection based on Spatial-Temporal-Textual point process
sub-package of spatstat containing core functionality for data analysis and modelling
Python Package for simulation and estimation of Hawkes processes
Sub-package of spatstat containing all datasets
3D object-based model of braided river deposits (marked point process), an open-source software package (R language)
Efficient point process inference for large scale object detection
Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Tools for evaluating the goodness of fit of a point process model via the time rescaling theorem
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