Implementations of quantum simulation algorithms MCMC and Langevin
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Updated
Sep 24, 2023 - Julia
Implementations of quantum simulation algorithms MCMC and Langevin
A collection of Monte Carlo sampling algorithms with application examples implemented in Julia
Codes and notebooks for the application of Markov Chain Monte Carlo in spinfoams. Computation of boundary observables, correlation functions and entanglement entropy.
City-scale car traffic and parking density maps from Uber Movement travel time data
Neural quantum states in Julia
Algorithms and case studies for the paper "Accelerating delayed-acceptance Markov chain Monte Carlo algorithms".
(Hierarchical) Phylogenetic Models in Julia
Julia implementation of elliptical slice sampling.
Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler
Piecewise Deterministic Sampler library (Bouncy particle sampler, Zig Zag sampler, ...)
Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection
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