Found 1737 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Loop-Cluster Monte Carlo Algorithm for Classical Statistical Models

We introduce a joint model of bond-occupation variables interacting with so-called $q$-flow variables. Expand abstract.
97 days ago
10/10 relevant
arXiv

Plateau Proposal Distributions for Adaptive Component-wise Multiple-Try Metropolis

Markov chain Monte Carlo (MCMC) methods are sampling methods that have become a commonly used tool in statistics, for example to perform Monte Carlo integration. Expand abstract.
97 days ago
4/10 relevant
arXiv

Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations

In many cases the data generating processes used in these Monte Carlo studies do not resemble real data sets and instead reflect many arbitrary decisions made by the researchers. Expand abstract.
98 days ago
10/10 relevant
arXiv

Self-learning Hybrid Monte Carlo: A First-principles Approach

We propose a novel approach called Self-Learning Hybrid Monte Carlo (SLHMC) which is a general method to make use of machine learning potentials to accelerate the statistical sampling of first-principles density-functional-theory (DFT) simulations. Expand abstract.
98 days ago
10/10 relevant
arXiv

A Monte Carlo method to estimate cell population heterogeneity

Here, we introduce a computational sampling method named "Contour Monte Carlo" for estimating mathematical model parameters from snapshot distributions, which is straightforward to implement and does not require cells be assigned to predefined categories. Expand abstract.
98 days ago
10/10 relevant
bioRxiv

Machine Learning in Least-Squares Monte Carlo Proxy Modeling of Life Insurance Companies

Since the industry is currently far from being endowed with sufficient computational capacities to fully simulate these distributions, the insurers have to rely on suitable approximation techniques such as the least-squares Monte Carlo (LSMC) method. Expand abstract.
99 days ago
10/10 relevant
arXiv

Real-frequency Diagrammatic Monte Carlo at Finite Temperature

Diagrammatic expansions are a central tool for treating correlated electron systems. Expand abstract.
104 days ago
10/10 relevant
arXiv

On the robustness of gradient-based MCMC algorithms

Langevin and Hamiltonian Monte Carlo) decays exponentially fast in the degree of mismatch between the scales of the proposal and target distributions, while for the random walk Metropolis (RWM) the decay is linear. Expand abstract.
104 days ago
4/10 relevant
arXiv

Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the substrate complexity and parameter choice on the reproducibility of results

The results presented in this work,along with the simulator developed, pave the way towards more realistic and reproducible Monte-Carlo simulations for Diffusion-Weighted MRI. Expand abstract.
105 days ago
10/10 relevant
arXiv

Deep neural network approximations for Monte Carlo algorithms

Having this in mind, one could aim for a general abstract result which shows under suitable assumptions that if a certain function can be approximated by any kind of (Monte Carlo) approximation scheme without the curse of dimensionality, then this function can also be approximated with DNNs without the curse of dimensionality. Expand abstract.
106 days ago
10/10 relevant
arXiv