27 papers · ranked by Valyu relevance
Wouter Boomsma, Jesper Ferkinghoff-Borg, Kresten Lindorff-Larsen, Michael Levitt
'Michael Levitt'] A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in…
Colin Young, Ganesh Subbarayan
In the present work, we propose using the cumulative distribution functions derived from maximum entropy formalisms, utilizing thermodynamic entropy as a measure of damage to fit the low-cycle fatigue data of metals. The thermodynamic entropy is measured from hysteresis loops of cyclic tension-compression fatigue tests…
Joshua Goodman
We show that maximum entropy (maxent) models can be modeled with certain kinds of HMMs, allowing us to construct maxent models with hidden variables, hidden state sequences, or other characteristics. The models can be trained using the forwardbackward algorithm. While the results are primarily of theoretical interest…
Sergio Davis, Joaquín Peralta, Yasmín Navarrete, Diego González + 1 more
'Gonzalo Gutiérrez'] The formalism used in describing the thermodynamics of abrupt (or first-order) phase transitions is reviewed as an application of maximum entropy inference. In this treatment, we show that the concepts of transition temperature, latent heat and entropy difference between phases will inevitably have…
Ulisse Ferrari, Tomoyuki Obuchi, Thierry Mora
The principle of maximum entropy provides a useful method for inferring statistical mechanics models from observations in correlated systems, and is widely used in a variety of fields where accurate data are available. While the assumptions underlying maximum entropy are intuitive and appealing, its adequacy for…
Dayi He, Ran Li, Qi Huang, Ping Lei + 1 more
In related research on queuing systems, in order to determine the system state, there is a widespread practice to assume that the system is stable and that distributions of the customer arrival ratio and service ratio are known information. In this study, the queuing system is looked at as a black box without any…
Andrea De Martino, Daniele De Martino
A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different…
Kenneth Bogert, Matthew Kothe
The principle of maximum entropy, as introduced by Jaynes in information theory,1 has contributed to advancements in various domains such as Statistical Mechanics,2 Machine Learning,3 and Ecology.4 Its resultant solutions have served as a catalyst, facilitating researchers in mapping their empirical observations to the…
Sergio Davis
—It is shown that a consistent application of Bayesian updating from a prior probability density to a posterior using evidence in the form of expectation constraints leads to exactly the same results as the application of the maximum entropy principle, namely a posterior belonging to the exponential family. The…
Giuseppe M. Ferro, Edwin Pos, Andrea Somazzi
G.M.F., A.S. and E.T.P. jointly conceived the study and designed the research. A.S. carried out the simulations and analysed the results. G.M.F. and E.T.P. developed the ecological and economic case studies and connected the framework to real-world examples. All authors contributed to writing the manuscript and…
Gregor Chliamovitch, Alexandre Dupuis, Anton Golub, Bastien Chopard
We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, at least in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is…
Mattia Miotto, Lorenzo Monacelli, Viola Folli, Giorgio Gosti + 1 more
'Edoardo Milanetti'] We present ToloMEo (TOpoLogical netwOrk Maximum Entropy Optimization), a program implemented in C and Python that exploits a maximum entropy algorithm to evaluate network topological information. ToloMEo can study any system defined on a connected network where nodes can assume N discrete values by…
Kenneth Bogert, Yikang Gui, Prashant Doshi
The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically estimated feature expectations. However, in many real-world applications that use noisy sensors computing the feature expectations may be…
Steve Pressé, Kingshuk Ghosh, Julian Lee, Ken A. Dill
Different quantities that go by the name of entropy are used in variational principles to infer probability distributions from limited data. Shore and Johnson showed that maximizing the Boltzmann-Gibbs form of the entropy ensures that probability distributions inferred satisfy the multiplication rule of probability for…
Nives Brajčić Kurbaša, Blaž Gotovac, Vedrana Kozulić, Hrvoje Gotovac + 1 more
'Philip Broadbridge'] Estimation of the probability density function from the statistical power moments presents a challenging nonlinear numerical problem posed by unbalanced nonlinearities, numerical instability and a lack of convergence, especially for larger numbers of moments. Despite many numerical improvements…
Purushottam D. Dixit
In modern biological physics, there is a great interest in building generative probabilistic models for ensembles of covarying binary variables. A popular approach is to use the maximum entropy principle. Here, one builds generative models that use as constraints lower level statistics estimated from the data. While…
John L. Schnase, Mark L. Carroll, Roger L. Gill, Glenn S. Tamkin + 4 more
MaxEnt is an important aid in understanding the influence of climate change on species distributions and abundance. There is growing interest in using IPCC-class global climate model outputs as environmental predictors in this work. These models provide realistic, global representations of the climate system…
Zahra Amini Farsani, Volker J. Schmid, Udo Von Toussaint
Background: For the kinetic models used in contrast-based medical imaging, the assignment of the arterial input function named AIF is essential for the estimation of the physiological parameters of the tissue via solving an optimization problem. Objective: In the current study, we estimate the AIF relayed on the…
Alireza Beygi, Haralampos Hatzikirou
By applying the principle of maximum entropy, we demonstrate the universality of the spatial distributions of the cone photoreceptors in the retinas of vertebrates. We obtain Lemaître’s law as a special case of our formalism.
Holger Metzler, Carlos A. Sierra, Jasper A. Vrugt, Anneli Guthke + 1 more
Mass-balanced compartmental systems defy classical deterministic entropy measures since both metric and topological entropy vanish in dissipative dynamics. By interpreting open compartmental systems as absorbing continuous-time Markov chains that describe the random journey of a single representative particle, we allow…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Authors not listed
Electrochemical impedance spectroscopy (EIS) coupled with distribution of relaxation times (DRT) analysis is a robust framework for characterizing electrochemical systems. However, DRT deconvolution is often plagued by spurious peaks, hindering accurate process identification and quantitative parameter estimation. To…
Ludger Starke, Dirk Ostwald
Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation…
Authors not listed
In quantum chemistry, diffusion-controlled reactions are typically characterized by a monotonous rise in the electronic energy, indicative of a barrierless process. In reality, this change in electronic energy is accompanied by an increase in entropy, thereby introducing a barrier in free energy. Standard…
Mohsen Farshad
Providing a simple description of entropy as the foundation of thermodynamics is necessary for researchers in explaining physical phenomena in the universe. Here we dive deep into the meaning of entropy starting from the basics and ending with the Newton's second law of motion which may be rooted in a hidden dimension…
Chenxi Sui, Ziyang Jiang, Genesis Higueros, David Carlson + 1 more
High-performance batteries are poised for electrification of vehicles and therefore mitigate greenhouse gas emissions, which, in turn, promote a sustainable future. However, the design of optimized batteries is challenging due to the nonlinear governing physics and electrochemistry. Recent advancements have…