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Recent advances in stochastic gradient variational inference have made it possible to perform variational Bayesian inference with posterior approximations containing auxiliary random variables. This enables us to explore a new synthesis of…

Computation · Statistics 2015-05-20 Tim Salimans , Diederik P. Kingma , Max Welling

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of…

Statistical Mechanics · Physics 2016-09-28 Sebastian C. Kapfer , Werner Krauth

We introduce ETOM, a five-level benchmark for evaluating multi-hop, end-to-end tool orchestration by LLM agents within a hierarchical Model-Context Protocol (MCP) ecosystem. Existing benchmarks often assess tools in isolation, overlooking…

Artificial Intelligence · Computer Science 2026-01-21 Jia-Kai Dong , I-Wei Huang , Chun-Tin Wu , Yi-Tien Tsai

In this project we initiate an investigation of the applicability of Quasi-Monte Carlo methods to lattice field theories in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an…

High Energy Physics - Lattice · Physics 2015-06-12 K. Jansen , H. Leovey , A. Nube , A. Griewank , M. Mueller-Preussker

In this article, a novel cluster analysis algorithm was employed in the study of polymer coil to globule transition via single chain Monte Carlo simulations. The algorithm, which has been recently applied in Molecular Dynamics simulations…

Soft Condensed Matter · Physics 2013-11-21 T. E. Raptis , Vasilios E. Raptis

Large, sparse linear systems are pervasive in modern science and engineering, and Krylov subspace solvers are an established means of solving them. Yet convergence can be slow for ill-conditioned matrices, so practical deployments usually…

Machine learning tools are commonly used in modern high energy physics (HEP) experiments. Different models, such as boosted decision trees (BDT) and artificial neural networks (ANN), are widely used in analyses and even in the software…

Data Analysis, Statistics and Probability · Physics 2016-12-21 A. Rogozhnikov

We present novel Monte Carlo methods for treating the interacting shell model that allow exact calculations much larger than those heretofore possible. The two-body interaction is linearized by an auxiliary field; Monte Carlo evaluation of…

Nuclear Theory · Physics 2008-11-26 C. W. Johnson , S. E. Koonin , G. H. Lang , W. E. Ormand

The use of ensemble Monte Carlo (EMC) methods for the simulation of transport in semiconductor devices has become extensive over the past few decades. This method allows for simulation utilizing particles while addressing the full physics…

Other Condensed Matter · Physics 2023-04-04 David K. Ferry

Typical design flows are hierarchical and rely on assembling many individual technology elements from standard cells to complete boards. Providers use compact models to provide simplified views of their products to their users. Designers…

Hardware Architecture · Computer Science 2021-04-23 Dan Alexandrescu , Aneesh Balakrishnan , Thomas Lange , Maximilien Glorieux

Model ensembling is a well-established technique for improving the performance of machine learning models. Conventionally, this involves averaging the output distributions of multiple models and selecting the most probable label. This idea…

Machine Learning · Computer Science 2026-05-26 Jiale Fu , Yuchu Jiang , Peijun Wu , Chonghan Liu , Joey Tianyi Zhou , Xu Yang

Adaptive sampling and planning in robotic environmental monitoring are challenging when the target environmental process varies over space and time. The underlying environmental dynamics require the planning module to integrate future…

Robotics · Computer Science 2023-06-19 Weizhe Chen , Lantao Liu

The purely numerical evaluation of multi-loop integrals and amplitudes can be a viable alternative to analytic approaches, in particular in the presence of several mass scales, provided sufficient accuracy can be achieved in an acceptable…

High Energy Physics - Phenomenology · Physics 2019-06-26 S. Borowka , G. Heinrich , S. Jahn , S. P. Jones , M. Kerner , J. Schlenk

RunMC is an object-oriented framework aimed to generate and to analyse high-energy collisions of elementary particles using Monte Carlo simulations. This package, being based on C++ adopted by CERN as the main programming language for the…

High Energy Physics - Phenomenology · Physics 2015-06-25 S. Chekanov

This program can be used to simulate polarised nucleon - nucleon collisions at high energies. Spins of colliding particles are taken into account. The program allows to calculate cross sections for various processes.

High Energy Physics - Phenomenology · Physics 2009-10-28 S. Guellenstern , P. Gornicki , L. Mankiewicz , A. Schaefer

This paper presents an efficient approach to object manipulation planning using Monte Carlo Tree Search (MCTS) to find contact sequences and an efficient ADMM-based trajectory optimization algorithm to evaluate the dynamic feasibility of…

Robotics · Computer Science 2023-03-21 Huaijiang Zhu , Avadesh Meduri , Ludovic Righetti

System-level design, once the province of board designers, has now become a central concern for chip designers. Because chip design is a less forgiving design medium -- design cycles are longer and mistakes are harder to correct --…

Hardware Architecture · Computer Science 2025-07-15 Shuvra S. Bhattacharyya , Marilyn Wolf

We discuss the recently proposed multicanonical multigrid Monte Carlo method and apply it to the scalar $\phi^4$-model on a square lattice. To investigate the performance of the new algorithm at the field-driven first-order phase…

High Energy Physics - Lattice · Physics 2009-10-28 Wolfhard Janke , Tilman Sauer

Computational modeling of contact is fundamental to many engineering applications, yet accurately and efficiently solving complex contact problems remains challenging. In this work, we propose a new contact algorithm that computes contact…

Computational Engineering, Finance, and Science · Computer Science 2025-09-11 Xinyu Wang , Weipeng Xu , Tianju Xue

A review of the Loop Algorithm, its generalizations, and its relation to some other Monte Carlo techniques is given. The loop algorithm is a Quantum Monte Carlo procedure which employs nonlocal changes of worldline configurations,…

Strongly Correlated Electrons · Physics 2014-10-13 H. G. Evertz
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