Efficient point process inference for large scale object detection
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Updated
Apr 3, 2018 - MATLAB
Efficient point process inference for large scale object detection
Simulates a random determinantally-thinned Poisson point process on a rectangle.
A novel point-process model to predict the course of epidemics and other saturating phenomena.
Generates height map and cities then constructs a sensible road network
Exploration of signal with non-overlapping rectangular pulses in the context of flicker noise.
Point process sensing library (sensepy)
A package for temporal point process modeling, simulation and inference (unmaintained)
Code for "Fast Bayesian Estimation of Point Process Intensity as Function of Covariates" at NeurIPS2022
Sub-package of spatstat containing all datasets
Causal Effect of Digital (First-time) Badges in Social Platforms
Analysis of point process driven by fractional Brownian motion.
Python Package for simulation and estimation of Hawkes processes
Dual Network Hawkes Process -- Analyzing Topic Transitions in Text-Based Social Cascades
Offers models and utilities for event time data using point processes.
Diffusion models of inter-event times in point processes.
Maximum likelihood estimation of Hawkes processes
Sample a repelled point process, compute a Monte Carlo estimation for the integral of a function using various variants of the Monte Carlo method including the Monte Carlo with a repelled point process, and visualize gravitational allocations 2D.
🧠 A decoder of Spike Trains using 🔬 Bayesian, State-Space, 📐 Point-Processes, EM-algorithm, Maximum-likelihood
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