jmwalchessen / neural_likelihood_interactive_app

This is an interactive app (run on local computer) to visualize neural likelihood surfaces from the paper "Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods"

Home Page:https://arxiv.org/abs/2305.04634

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Interactive App for Neural Likelihood

This is an interactive app (run on local computer) to visualize neural likelihood surfaces from the paper:

J. Walchessen, A. Lenzi, and M. Kuusela. Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods. Preprint arXiv:2305.04634 [stat.ME], 2023. arxiv preprint

Contact Julia Walchessen at jwalches@andrew.cmu.edu with any questions.

Structure

This code will generate a webpage (running via local host) which you can then use to generate simulated data from spatial processes and their corresponding neural likelihood surfaces. To run webpage, use command: python main.py. On the webpage, select the tab Gaussian Process. Enter in the variables for seed value and the parameters of a Gaussian process with exponential kerne (length scale and variance). Note that length scale and variance should be numbers between 0 and 2 and have at most 2 decimal places. Press enter and after approximately (10 seconds to a few minutes depending on your laptop capibilities), a visualization of a realization of a Gaussian Process on a 25 by 25 grid will appear and the corresponding exact, uncalibrated neural, and calibrated neural likelihood surfaces. So far, we do not have code for Brown--Resnick processes.

The package requirements to run this code are in requirements.txt

About

This is an interactive app (run on local computer) to visualize neural likelihood surfaces from the paper "Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods"

https://arxiv.org/abs/2305.04634


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