3 papers
cs.DC2025
Acceleration of Parallel Tempering for Markov Chain Monte Carlo methods
Aingeru Ramos, Jose A Pascual, Javier Navaridas +1
Markov Chain Monte Carlo methods are algorithms used to sample probability distributions, commonly used to sample the Boltzmann distribution of physical/chemical models (e.g., prot…
quant-ph2025
On the Convergence of Markov Chain Distribution within Quantum Walk Circuit Subspace
Aingeru Ramos, Jose A. Pascual, Javier Navaridas +1
Markov Chain Monte Carlo (MCMC) methods are algorithms for sampling probability distributions, commonly applied to the Boltzmann distribution in physical and chemical models such a…
cs.LG2025
GLow -- A Novel, Flower-Based Simulated Gossip Learning Strategy
Aitor Belenguer, Jose A. Pascual, Javier Navaridas
Fully decentralized learning algorithms are still in an early stage of development. Creating modular Gossip Learning strategies is not trivial due to convergence challenges and Byz…