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Resampling techniques are widely used in statistical inference and ensemble learning, in which estimators' statistical properties are essential. However, existing methods are computationally demanding, because repetitions of…

Machine Learning · Statistics 2019-05-24 Takashi Takahashi , Yoshiyuki Kabashima

For random-walk Metropolis (RWM) and parallel tempering (PT) algorithms, an asymptotic acceptance rate of around 0.234 is known to be optimal in certain high-dimensional limits. However, its practical relevance is uncertain due to…

Computation · Statistics 2025-08-05 Aidan Li , Liyan Wang , Tianye Dou , Jeffrey S. Rosenthal

Recent advances in random-walk particle-tracking have enabled direct simulation of mixing and reactions on particles by allowing the particles to interact with each other using a multi-point mass transfer scheme. The mass transfer scheme…

Computational Physics · Physics 2019-04-22 Nicholas B. Engdahl , Michael J. Schmidt , David A. Benson

We investigate the theoretical foundations of the simulated tempering method and use our findings to design efficient algorithms. Employing a large deviation argument first used for replica exchange molecular dynamics [Plattner et al., J.…

Chemical Physics · Physics 2019-02-08 Anton Martinsson , Jianfeng Lu , Benedict Leimkuhler , Eric Vanden-Eijnden

Trajectory optimizers for model-based reinforcement learning, such as the Cross-Entropy Method (CEM), can yield compelling results even in high-dimensional control tasks and sparse-reward environments. However, their sampling inefficiency…

The computer simulation of many molecular processes is complicated by long time scales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare events, which combines transition path…

Computational Physics · Physics 2023-03-23 Sebastian Falkner , Alessandro Coretti , Christoph Dellago

We introduce a generic, parallel Wang-Landau method that is naturally suited to implementation on massively parallel, petaflop supercomputers. The approach introduces a replica-exchange framework in which densities of states for overlapping…

Computational Physics · Physics 2015-06-18 Ying Wai Li , Thomas Vogel , Thomas Wüst , David P. Landau

The replica method is applied to a neural network model with state-dependent synapses built from those patterns having a correlation with the state of the system greater than a certain threshold. Replica-symmetric and first-step…

Disordered Systems and Neural Networks · Physics 2009-10-31 D. Bollé , G. M. Shim , B. Van Mol

The widespread popularity of replica exchange and expanded ensemble algorithms for simulating complex molecular systems in chemistry and biophysics has generated much interest in enhancing phase space mixing of these protocols, thus…

Statistical Mechanics · Physics 2011-12-06 John D. Chodera , Michael R. Shirts

The random field Ising model with Gaussian disorder is studied using a new Monte Carlo algorithm. The algorithm combines the advantanges of the replica exchange method and the two-replica cluster method and is much more efficient than the…

Statistical Mechanics · Physics 2009-10-31 Jon Machta , Mark Newman , Lincoln Chayes

We propose a class of models of random walks in a random environment where an exact solution can be given for a stationary distribution. The tool is the detailed balance equations.

Probability · Mathematics 2015-05-27 M. Gannon , E. Pechersky , Y. Suhov , A. Yambartsev

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a…

Machine Learning · Computer Science 2012-10-19 Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht

Random Walks in Cooling Random Environments (RWCRE) is a model of random walks in dynamic random environments where the entire environment is resampled along a fixed sequence of times, called the "cooling sequence," and is kept fixed in…

Probability · Mathematics 2021-08-20 Luca Avena , Conrado da Costa , Jonathon Peterson

We present an adaptive multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The algorithm design is based on a two-level parallelization scheme that allows the method to scale its performance in…

Computational Physics · Physics 2016-08-10 C. A. Navarro , Wei Huang , Youjin Deng

We propose a new Monte Carlo method for efficiently sampling trajectories with fixed initial and final conditions in a system with discrete degrees of freedom. The method can be applied to any stochastic process with local interactions,…

Statistical Mechanics · Physics 2012-03-30 Thierry Mora , Aleksandra M. Walczak , Francesco Zamponi

In a random ray method of neutral particle transport simulation, each iteration begins by sampling a set of rays before proceeding to solve the characteristic transport equation along the linear paths the rays follow. Historically,…

Computational Physics · Physics 2025-01-13 Samuel Pasmann , John Tramm

We have developed a technique to accelerate the acquisition of effectively uncorrelated configurations for off-lattice models of dense polymer melts which makes use of both parallel tempering and large scale Monte Carlo moves. The method is…

Soft Condensed Matter · Physics 2009-10-31 Alex Bunker , Burkhard Duenweg

In this letter, we emulate real-world statistics for mobility patterns on road systems. We then propose modifications to the assumptions of the random waypoint (RWP) model to better represent high-mobility profiles. We call the model under…

Information Theory · Computer Science 2021-09-14 Hussein A. Ammar , Raviraj Adve , Shahram Shahbazpanahi , Gary Boudreau , Kothapalli Venkata Srinivas

Random walk is an explainable approach for modeling natural processes at the molecular level. The Random Permutation Set Theory (RPST) serves as a framework for uncertainty reasoning, extending the applicability of Dempster-Shafer Theory.…

Artificial Intelligence · Computer Science 2024-09-27 Jiefeng Zhou , Zhen Li , Yong Deng

We propose two efficient algorithms for configurational sampling of systems with rough energy landscape. The first one is a new method for the determination of the multicanonical weight factor. In this method a short replica-exchange…

Statistical Mechanics · Physics 2009-10-31 Yuji Sugita , Yuko Okamoto