English
Related papers

Related papers: Fundamental View on the Calculation of Internal Pa…

200 papers

Probabilistic inference provides a language for describing how organisms may learn from and adapt to their environment. The computations needed to implement probabilistic inference often require specific representations, akin to having the…

Molecular Networks · Quantitative Biology 2018-06-28 Yarden Katz , Michael Springer , Walter Fontana

This letter aims at justifying the stochastic equations in terms of the number density variable, which are still controversial, via complementing Dean's approach [Dean D S 1996 {\itshape J. Phys. A} {\bf 29} L613]. Our course is twofold:…

Disordered Systems and Neural Networks · Physics 2009-10-31 H. Frusawa , R. Hayakawa

We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations…

Machine Learning · Statistics 2016-09-14 Bernhard Schölkopf , Krikamol Muandet , Kenji Fukumizu , Jonas Peters

We consider random normal matrix and planar symplectic ensembles, which can be interpreted as two-dimensional Coulomb gases having determinantal and Pfaffian structures, respectively. For general radially symmetric potentials, we derive the…

Probability · Mathematics 2023-03-22 Sung-Soo Byun , Nam-Gyu Kang , Seong-Mi Seo

An important class of fractional differential and integral operators is given by the theory of fractional calculus with respect to functions, sometimes called $\Psi$-fractional calculus. The operational calculus approach has proved useful…

Classical Analysis and ODEs · Mathematics 2020-08-11 Hafiz Muhammad Fahad , Mujeeb ur Rehman , Arran Fernandez

Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. This paper investigates how classical inference and learning tasks known from the graphical model community can be tackled for…

Artificial Intelligence · Computer Science 2020-02-19 Daan Fierens , Guy Van den Broeck , Joris Renkens , Dimitar Shterionov , Bernd Gutmann , Ingo Thon , Gerda Janssens , Luc De Raedt

Given a graphical model (GM), computing its partition function is the most essential inference task, but it is computationally intractable in general. To address the issue, iterative approximation algorithms exploring certain local…

Machine Learning · Computer Science 2019-05-15 Sejun Park , Eunho Yang , Se-Young Yun , Jinwoo Shin

We study the complexity of approximately evaluating the Ising and Tutte partition functions with complex parameters. Our results are partly motivated by the study of the quantum complexity classes BQP and IQP. Recent results show how to…

Computational Complexity · Computer Science 2017-01-24 Leslie Ann Goldberg , Heng Guo

Partition functions of a canonical ensemble of non-interacting bound electrons are a key ingredient of the super-transition-array approach to the computation of radiative opacity. A few years ago, we published a robust and stable recursion…

Statistical Mechanics · Physics 2020-10-28 Jean-Christophe Pain , Franck Gilleron , Brian G. Wilson

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform…

Chemical Physics · Physics 2018-03-19 Pascal Pernot , Andreas Savin

A formula for supershell partition functions, which play a major role in the Super Transition Array approach to radiative-opacity calculations, is derived as a functional of the distribution of energies within the supershell. It consists in…

Atomic Physics · Physics 2023-06-05 Bran G. Wilson , Jean-Christophe Pain

We consider the problem of approximating partition functions for Ising models. We make use of recent tools in combinatorial optimization: the Sherali-Adams and Lasserre convex programming hierarchies, in combination with variational methods…

Machine Learning · Computer Science 2016-07-13 Andrej Risteski

Physical Unclonable Functions can be used for secure key generation in cryptographic applications. It is explained how methods from coding theory must be applied in order to ensure reliable key regeneration. Based on previous work, we show…

Information Theory · Computer Science 2014-07-31 Sven Müelich , Sven Puchinger , Martin Bossert , Matthias Hiller , Georg Sigl

We calculate the partition function for "composite particles". For any finite number of states d, and in the following two cases: 1)all states have the same energy, 2)the energy is linearly distributed over the states, we transform the…

Condensed Matter · Physics 2007-05-23 M. Bergère

New method is developed for calculation of single-particle occupation numbers in finite Fermi systems of interacting particles. It is more accurate than the canonical distribution method and gives the Fermi-Dirac distribution in the limit…

Statistical Mechanics · Physics 2009-10-28 V. V. Flambaum , F. M. Izrailev

We demonstrate that statistics for several types of set partitions are described by generating functions which appear in the theory of integrable equations.

Exactly Solvable and Integrable Systems · Physics 2017-05-30 V. E. Adler

A large proportion of organic molecules relevant to medicine and biotechnology contain one or more ionizable groups, which means that fundamental physical and chemical properties (e.g. the charge of the molecule) depend on the pH of the…

Chemical Physics · Physics 2015-12-03 Jan H. Jensen

We prove functional limits theorems for the occupation time process of a system of particles moving independently in $R^d$ according to a symmetric $\alpha$-stable L\'evy process, and starting off from an inhomogeneous Poisson point measure…

Probability · Mathematics 2012-03-14 Tomasz Bojdecki , Luis G. Gorostiza , Anna Talarczyk

Probabilistic power flow (PPF) is essential for quantifying operational uncertainty in modern distribution systems with high penetration of renewable generation and flexible loads. Conventional PPF methods primarily rely on Monte Carlo (MC)…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Weijie Xia , James Ciyu Qin , Edgar Mauricio Salazar Duque , Hongjin Du , Peter Palensky , Giovanni Sansavini , Pedro P. Vergara
‹ Prev 1 4 5 6 7 8 10 Next ›