Algorithms for solving circuit-fault-diagnosis problems
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Updated
Nov 19, 2019 - Python
Algorithms for solving circuit-fault-diagnosis problems
Replica Exchange Monte Carlo using PyStan2
Hamon provides GPU-accelerated block Gibbs, adaptive non-reversible parallel tempering, and full round-trip diagnostics to drive scientific discovery in physics, probabilistic ML, and hard combinatorial problems.
Algorithm for ATSP using SA and PT algorithms
Python implementations of computational statistical mechanics and energy-based machine learning algorithms based on the UIUC PHYS 498 CMP curriculum. Covers Ising Model simulations, Renormalization Group flows, Parallel Tempering, Hopfield Networks, and Restricted Boltzmann Machines.
Combinatorial optimization with Parallel Tempering, Dimer Lattice, and high-precision geometry
Convert combinatorial problems to Ising/QUBO form and solve them with a fast Rust simulated-annealing & parallel-tempering kernel.
Development of spot modeling code for Kepler data.
minimal ring model with algebraic frustration floor
Parallel tempering / replica exchange orchestrator for mchammer Monte Carlo simulations with icet cluster expansions
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