High Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data
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Updated
May 25, 2024 - Julia
High Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data
Distributed and parallel sampling from intractable distributions
This repository contains the Python code associated with the scientific publication "Exploring Quantum Annealing Architectures: A Spin Glass Perspective".
JuMP wrapper for NASA PySA (ft QUBODrivers.jl)
Receiver function inversion by reversible-jump Markov-chain Monte Carlo
Latent Dirichlet Allocation coupled with Bayesian Time Series analyses
Algorithm for ATSP using SA and PT algorithms
Examples of several Markov Chain Monte Carlo methods such as t walk, emcee,Hamiltonian MC, Parallel Tempering HMC applied to UQ in ODEs
These are codes of toy physics models that contain building blocks for understanding the concept behind EVCCPMC
Parallel tempering code for an Ising spin glass (fortran90)
Variance reduction in energy estimators accelerates the exponential convergence in deep learning (ICLR'21)
Code for ABC-APTMC paper
Replica Exchange Monte Carlo using PyStan2
Langevin Gradient Parallel Tempering for Bayesian Neural Learning.
Algorithms for solving circuit-fault-diagnosis problems
Development of spot modeling code for Kepler data.
Bayeisan inversion to recover Green's functions of receiver-side structures from teleseismic waveforms
Parallel Tempering Metropolis Monte Carlo
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