Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport

Last update: Nov 08, 2021

Related tags

Overview

Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport

This GitHub page provides code for reproducing the results in Section 4.2 of the manuscript titled Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport by Tin Lok James Ng and Andrew Zammit-Mangion. The manuscript describes the use of normalizing flows, specifically radial flows, to model the intensity function of a non-homogeneous point process on the sphere.

The figure below depicts results from modeling the end locations of cyclone data in the North Pacific Ocean using the normalizing flows. The center panel shows the intensity-function estimate, while the left and right panels depict the empirical 10 and 90 percentiles of the bootstrap distribution of the intensity function, respectively.

Instructions

Please note the following if proceeding to reproduce the results in Section 4.2.

Software requirements: R (>=3.6), Python (>=3.7), PyTorch, Numpy

Hardware requirements: >= 16GB of RAM. Multiple cores could be used with slight code modification to parallelize the fitting and bootstrapping procedures.

Contents:

pacific.csv Data containing the end locations of cyclones ni the North Pacific Ocean
sphere_pp_vec.py Fits the model to the cyclone locations data
sphere_est_avg.py Obtains the ensemble average from the model fits
sphere_np_boot.py Obtain nonparametric bootstrap estimates
sphere_np_percentile.py Obtain the 10th and 90th percentiles from nonparametric bootstrap estimates
plot_est_intensity.R Plots the estimated intensity function
plot_np_lower.R Plots the empirical 10 percentile of the bootstrap distribution
plot_np_upper.R Plots the empirical 90 percentile of the bootstrap distribution
run_all.sh A bash script that runs all of the above

Notes: Please run the bash script run_all.sh or the scripts below in the following order:

sphere_pp_vec.py
sphere_est_avg.py
sphere_np_boot.py
sphere_np_percentile.py
plot_est_intensity.R
plot_np_lower.R
plot_np_upper.R

This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].

CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req

10 Sep 12, 2022

A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

110 Dec 27, 2022

Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)

Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen

42 Nov 24, 2022

This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.

NoW Evaluation This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard e

71 Dec 30, 2022

Automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azure

fwhr-calc-website This project is to automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azur

1 Feb 7, 2022

$Measure WWjj polarization fraction$

Measure WWjj polarization fraction

WlWl Polarization Measure WWjj polarization fraction Paper: arXiv:2109.09924 Notice: This code can only be used for the inference process, if you want

4 Apr 10, 2022

ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.

The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio

23 Oct 9, 2022

A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection 1. 介绍用以替代 NMS，在所有 bbox 中挑选出最优的集合。 NMS 仅考虑了 bbox 的得分，然后根据 IOU 来

44 Sep 15, 2022

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

170 Dec 27, 2022

Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport

Related tags

Overview

Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport

Instructions

You might also like...

This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].

A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.

Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)

Automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azure

Measure WWjj polarization fraction

ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.

A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Releases(1.0)

1.0(Nov 9, 2021)

Owner

Andrew Zammit Mangion

Image Deblurring using Generative Adversarial Networks

code for Fast Point Cloud Registration with Optimal Transport

A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

2021 National Underwater Robotics Vision Optics

Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021.

🚗 INGI Dakar 2K21 - Be the first one on the finish line ! 🚗

VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning

Build a medical knowledge graph based on Unified Language Medical System (UMLS)

subpixel: A subpixel convnet for super resolution with Tensorflow

[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"

Jiminy Cricket Environment (NeurIPS 2021)

Reproducing Results from A Hybrid Approach to Targeting Social Assistance

Running Google MoveNet Multipose Tracking models on OpenVINO.

Code corresponding to The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

Official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

Summary of related papers on visual attention

C3D is a modified version of BVLC caffe to support 3D ConvNets.

Official code repository for A Simple Long-Tailed Rocognition Baseline via Vision-Language Model.

GANsformer: Generative Adversarial Transformers Drew A