Sampling from intractable distributions, with support for distributed and parallel methods
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Updated
Nov 23, 2024 - Julia
Sampling from intractable distributions, with support for distributed and parallel methods
High Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data
Receiver function inversion by reversible-jump Markov-chain Monte Carlo
Latent Dirichlet Allocation coupled with Bayesian Time Series analyses
Bayeisan inversion to recover Green's functions of receiver-side structures from teleseismic waveforms
Variance reduction in energy estimators accelerates the exponential convergence in deep learning (ICLR'21)
Examples of several Markov Chain Monte Carlo methods such as t walk, emcee,Hamiltonian MC, Parallel Tempering HMC applied to UQ in ODEs
Langevin Gradient Parallel Tempering for Bayesian Neural Learning.
Algorithms for solving circuit-fault-diagnosis problems
Parallel Tempering Metropolis Monte Carlo
Replica Exchange Monte Carlo using PyStan2
Parallel tempering code for an Ising spin glass (fortran90)
JuMP wrapper for NASA PySA (ft QUBODrivers.jl)
This repository contains the Python code associated with the scientific publication "Exploring Quantum Annealing Architectures: A Spin Glass Perspective".
Code for ABC-APTMC paper
Algorithm for ATSP using SA and PT algorithms
Development of spot modeling code for Kepler data.
These are codes of toy physics models that contain building blocks for understanding the concept behind EVCCPMC
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