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Found 3 papers, 1 papers with code
Accurate Data-Driven Surrogates of Dynamical Systems for Forward Propagation of Uncertainty
Stochastic collocation (SC) is a well-known non-intrusive method of constructing surrogate models for uncertainty quantification.
Continuous-variable neural-network quantum states and the quantum rotor model
We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization.
Efficient MCMC Sampling for Bayesian Matrix Factorization by Breaking Posterior Symmetries
This choice of prior leads to simple implementations; however it also causes symmetries in the posterior distribution that can severely reduce the efficiency of Markov-chain Monte-Carlo (MCMC) sampling approaches.
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