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We compute the pressure of the random energy model (REM) and generalized random energy model(GREM) by establishing variational upper and lower bounds. For the upper bound, we generalize Guerra's ``broken replica symmetry bounds",and…

Mathematical Physics · Physics 2015-09-29 Cristian Giardina' , Shannon Starr

Conditional distribution is a fundamental quantity for describing the relationship between a response and a predictor. We propose a Wasserstein generative approach to learning a conditional distribution. The proposed approach uses a…

Machine Learning · Computer Science 2021-12-21 Shiao Liu , Xingyu Zhou , Yuling Jiao , Jian Huang

In a closed economic system, money is conserved. Thus, by analogy with energy, the equilibrium probability distribution of money must follow the exponential Gibbs law characterized by an effective temperature equal to the average amount of…

Statistical Mechanics · Physics 2009-02-25 Adrian Dragulescu , Victor M. Yakovenko

In order to overcome the problem of item nonresponse, random imputation methods are often used because they tend to preserve the distribution of the imputed variable. Among the random imputation methods, the random hot-deck has the…

Methodology · Statistics 2022-02-09 Caren Hasler , Yves Tillé

Gradient-based Discrete Samplers (GDSs) are effective for sampling discrete energy landscapes. However, they often stagnate in complex, non-convex settings. To improve exploration, we introduce the Discrete Replica EXchangE Langevin…

Machine Learning · Computer Science 2025-05-21 Haoyang Zheng , Hengrong Du , Ruqi Zhang , Guang Lin

Computing the equilibrium properties of complex systems, such as free energy differences, is often hampered by rare events in the dynamics. Enhanced sampling methods may be used in order to speed up sampling by, for example, using high…

Computational Physics · Physics 2015-02-11 Antonia S. J. S. Mey , Hao Wu , Frank Noé

We introduce a general framework for testing goodness-of-fit for Gaussian graphical models in both the low- and high-dimensional settings. This framework is based on a novel algorithm for generating exchangeable copies by conditioning on…

Methodology · Statistics 2025-01-07 Xiaotong Lin , Weihao Li , Fangqiao Tian , Dongming Huang

We discuss multi-dimensional generalizations of multicanonical algorithm, simulated tempering, and replica-exchange method. We generalize the original potential energy function $E_0$ by adding any physical quantity $V$ of interest as a new…

Statistical Mechanics · Physics 2008-10-08 Ayori Mitsutake , Yuko Okamoto

We consider an array of random variables, taking values in a complete and separable metric space, that exhibits a kind of symmetry which we call row exchangeability. Given such an array, a natural model for Bayesian nonparametric inference…

Statistics Theory · Mathematics 2025-10-10 Evan Donald , Jason Swanson

The continuous random energy model (CREM) is a toy model of disordered systems introduced by Bovier and Kurkova in 2004 based on previous work by Derrida and Spohn in the 80s. In a recent paper by Addario-Berry and Maillard, they raised the…

Probability · Mathematics 2023-08-03 Fu-Hsuan Ho

Differential equations (DEs) are crucial for modeling the evolution of natural or engineered systems. Traditionally, the parameters in DEs are adjusted to fit data from system observations. However, in fields such as politics, economics,…

Machine Learning · Computer Science 2024-12-30 Hyunwoo Cho , Sung Woong Cho , Hyeontae Jo , Hyung Ju Hwang

The Equi-Energy Sampler (EES) introduced by Kou et al [2006] is based on a population of chains which are updated by local moves and global moves, also called equi-energy jumps. The state space is partitioned into energy rings, and the…

Methodology · Statistics 2012-03-05 Meili Baragatti , Agnès Grimaud , Denys Pommeret

We propose a discrete transition-based reweighting analysis method (dTRAM) for analyzing configuration-space-discretized simulation trajectories produced at different thermodynamic states (temperatures, Hamiltonians, etc.) dTRAM provides…

Data Analysis, Statistics and Probability · Physics 2015-06-23 Hao Wu , Antonia S. J. S. Mey , Edina Rosta , Frank Noé

Seismic tomography solves high-dimensional optimization problems to image subsurface structures of Earth. In this paper, we propose to use random batch methods to construct the gradient used for iterations in seismic tomography.…

Numerical Analysis · Mathematics 2023-02-14 Yixiao Hu , Lihui Chai , Zhongyi Huang , Xu Yang

We introduce a new class of nonparametric prior distributions on the space of continuously varying densities, induced by Dirichlet process mixtures which diffuse in time. These select time-indexed random functions without jumps, whose…

Methodology · Statistics 2016-02-10 Ramsés H. Mena , Matteo Ruggiero

In this paper, a nonsmooth semilinear parabolic partial differential equation (PDE) is considered. For a reduced basis (RB) approach, a space-time formulation is used to develop a certified a-posteriori error estimator. This error estimator…

Numerical Analysis · Mathematics 2022-12-29 Marco Bernreuther , Stefan Volkwein

Energy-based models (EBMs) offer a flexible framework for probabilistic modelling across various data domains. However, training EBMs on data in discrete or mixed state spaces poses significant challenges due to the lack of robust and fast…

Machine Learning · Statistics 2024-12-03 Tobias Schröder , Zijing Ou , Yingzhen Li , Andrew B. Duncan

In this paper, we propose a coupled Discrete Empirical Interpolation Method (DEIM) and Generalized Multiscale Finite element method (GMsFEM) to solve nonlinear parabolic equations with application to the Allen-Cahn equation. The Allen-Cahn…

Numerical Analysis · Mathematics 2020-06-26 Yiran Wang , Eric Chung , Shubin Fu

Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) simulations. Path reweighting extends their output,…

Chemical Physics · Physics 2026-05-15 Titus S. van Erp , Daniel T. Zhang , Elias Wils , Sina Safaei , An Ghysels

We describe a very simple method for `consistent sampling' that allows for sampling with replacement. The method extends previous approaches to consistent sampling, which assign a pseudorandom real number to each element, and sample those…

Data Structures and Algorithms · Computer Science 2018-08-31 Ronald L. Rivest
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