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Approximate Bayesian Computation is widely used to infer the parameters of discrete-state continuous-time Markov networks. In this work, we focus on models that are governed by the Chemical Master Equation (the CME). Whilst originally…

Quantitative Methods · Quantitative Biology 2020-01-10 Christopher Lester

Image retargeting, which resizes images to one with a prescribed aspect ratio by determining an optimal warping map, has gained substantial interest in imaging science. Despite significant advances, existing methods often fail to ensure…

Numerical Analysis · Mathematics 2025-10-16 Chengyang Liu , Michael K. Ng

Energy-based models for discrete domains, such as graphs, explicitly capture relative likelihoods, naturally enabling composable probabilistic inference tasks like conditional generation or enforcing constraints at test-time. However,…

In real life, we frequently come across data sets that involve some independent explanatory variable(s) generating a set of ordinal responses. These ordinal responses may correspond to an underlying continuous latent variable, which is…

Methodology · Statistics 2024-01-08 Arijit Pyne , Subhrajyoty Roy , Abhik Ghosh , Ayanendranath Basu

The thermal sensitive electrical parameter (TSEP) method is crucial for enhancing the reliability of power devices through junction temperature monitoring. The TSEP method comprises three key processes: calibration, regression, and…

Machine Learning · Computer Science 2025-01-10 Qinghao Zhang , Wenrui Li , Pinjia Zhang

This Letter presents a neural estimator for entropy production, or NEEP, that estimates entropy production (EP) from trajectories of relevant variables without detailed information on the system dynamics. For steady state, we rigorously…

Statistical Mechanics · Physics 2020-10-06 Dong-Kyum Kim , Youngkyoung Bae , Sangyun Lee , Hawoong Jeong

The probability distribution describing the state of a Stochastic Reaction Network evolves according to the Chemical Master Equation (CME). It is common to estimated its solution using Monte Carlo methods such as the Stochastic Simulation…

Quantitative Methods · Quantitative Biology 2015-06-18 Benjamin Hepp , Ankit Gupta , Mustafa Khammash

Buildings rarely perform as designed/simulated and and there are numerous tangible benefits if this gap is reconciled. A new scientific yet pragmatic methodology - called Enhanced Parameter Estimation (EPE) - is proposed that allows…

Systems and Control · Electrical Eng. & Systems 2021-03-15 Kris Subbarao , Srijan Didwania , T. Agami Reddy , Marlin Addison

The efficiency of minimum-energy configuration searching algorithms is closely linked to the energy landscape structure of complex systems. Here we characterize this structure by following the time evolution of two systems, vacancy…

The minimum rate of entropy production (MREP) and the least dissipation energy (LDE) principles are re-examined concerning continuous systems in stationary nonequilibrium states. By means of simple considerations on coefficients of…

Classical Physics · Physics 2009-06-04 M. Salis

Continuous conformal transformation minimizes the conformal energy. The convergence of minimizing discrete conformal energy when the discrete mesh size tends to zero is an open problem. This paper addresses this problem via a careful error…

Numerical Analysis · Mathematics 2022-10-21 Zhenyue Zhang , Zhong-Heng Tan

Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowledge of the behaviour of natural and engineered systems. In…

We present a state-space-based path integral method to calculate the rate of electron transfer (ET) in multi-state, multi-electron condensed-phase processes. We employ an exact path integral in discrete electronic states and continuous…

Chemical Physics · Physics 2016-06-07 Jessica Ryan Duke , Nandini Ananth

In various practical situations, we encounter data from stochastic processes which can be efficiently modelled by an appropriate parametric model for subsequent statistical analyses. Unfortunately, the most common estimation and inference…

Methodology · Statistics 2022-04-12 Rohan Hore , Abhik Ghosh

Numerical studies of ionic motion through solid electrolytes commonly involve static nudged-elastic band (NEB) methods or costly \emph{ab initio} molecular dynamics (AIMD). Building on a time-local model of current carrier-electrolyte…

Materials Science · Physics 2025-04-10 Aleksandr Rodin , Ben Andrew Olsen , Andrey Ustyuzhanin , Artem Maevskiy

Chemical reactions are often associated with an energy barrier along the reaction pathway which hinders the spontaneity of the reaction. Changing the energy barrier along the reaction pathway allows one to modulate the performance of a…

Computational Physics · Physics 2018-09-26 Sudipta Kundu , Satadeep Bhattacharjee , Seung-Cheol Lee , Manish Jain

Several different methods exist for efficient approximation of paths in multiscale stochastic chemical systems. Another approach is to use bursts of stochastic simulation to estimate the parameters of a stochastic differential equation…

Numerical Analysis · Mathematics 2014-12-19 Simon Cotter , Radek Erban

Using dimensionally reduced models for the numerical simulation of thin objects is highly attractive as this reduces the computational work substantially. The case of narrow thin elastic bands is considered and a convergent finite element…

Numerical Analysis · Mathematics 2019-11-20 Sören Bartels

We continue the investigation of kinetic models of a system in contact via stochastic interactions with several spatially homogeneous thermal reservoirs at different temperatures. Considering models different from those investigated in…

Mathematical Physics · Physics 2017-04-18 Eric A. Carlen , Raffaelle Esposito , Joel L. Lebowitz , Rossana Marra , Clement Mouhot

We study minimum-energy pathways (MEPs) between the branches of metastable helical structures in chiral nematic liquid crystals (CNLCs)subjected to the electric field applied across the cell. By performing stability analysis we have found…

Soft Condensed Matter · Physics 2020-11-05 Semen S. Tenishchev , Ivan M. Tambovtcev , Alexei D. Kiselev , Valery M. Uzdin
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