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We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via…

Methodology · Statistics 2020-11-16 Alessandro Zito , Tommaso Rigon , Otso Ovaskainen , David Dunson

The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…

Materials Science · Physics 2021-10-04 Krishnendu Mukherjee , Alexander W. Dowling , Yamil Colón

Cayley's formula is a fundamental result in combinatorics that counts the number of labeled trees on n vertices. While existing proofs use approaches such as Prufer sequences and the Matrix-Tree Theorem, we give a combinatorial proof that…

Combinatorics · Mathematics 2026-02-11 Helia Karisani , Mohammadreza Daneshvaramoli

The adsorption of polymer and surfactant molecules onto colloidal particles or droplets in solution can be characterized non-destructively by scattering techniques. In a first part, the general framework of Dynamic Light Scattering, Small…

Soft Condensed Matter · Physics 2007-05-24 Julian Oberdisse

We introduce a sequential model for the deposition and aggregation of particles in the submonolayer regime. Once a particle has been randomly deposited on the substrate, it sticks to the closest atom or island within a distance \ell,…

Statistical Mechanics · Physics 2007-05-23 Paolo Politi , Yukio Saito

A simple molecular thermodynamic approach is applied to the study of the adsorption of gases of chain molecules on solid surfaces. We use a model based on the Statistical Associating Fluid Theory for Variable Range (SAFT-VR) potentials [A.…

Computational Physics · Physics 2010-12-23 M. Castro , R. Martinez , A. Martinez , H. C. Rosu

We develop an iterative framework for Bayesian inference problems where the posterior distribution may involve computationally intensive models, intractable gradients, significant posterior concentration, and pronounced non-Gaussianity. Our…

Computation · Statistics 2026-03-16 Daniel Sharp , Bart van Bloemen Waanders , Youssef Marzouk

Density-dependent diffusion is a widespread phenomenon in nature. We have examined the density-dependent diffusion behavior of some biological processes such as tumor growth and invasion [23]. Here, we extend our previous work by developing…

Statistical Mechanics · Physics 2022-02-14 Ahmed M. Fouad , Marwa M. Fouad

We propose Partition Tree, a novel tree-based framework for conditional density estimation over general outcome spaces that supports both continuous and categorical variables within a unified formulation. Our approach models conditional…

Machine Learning · Computer Science 2026-05-13 Felipe Angelim , Alessandro Leite

This work presents a novel diffusion based dual-phase molecular communication system where the source leverages multiple cooperating nanomachines to improve the end-to-end reliability of communication. The Neyman-Pearson Likelihood Ratio…

Information Theory · Computer Science 2017-10-17 Neeraj Varshney , Adarsh Patel , Aditya K. Jagannatham

The variation of the optical absorption of carbon nanotubes with their geometry has been a long standing question at the heart of both metrological and applicative issues, in particular because optical spectroscopy is one of the primary…

This paper introduces Tree-Pyramidal Adaptive Importance Sampling (TP-AIS), a novel iterated sampling method that outperforms state-of-the-art approaches like deterministic mixture population Monte Carlo (DM-PMC), mixture population Monte…

Machine Learning · Statistics 2020-03-25 Javier Felip , Nilesh Ahuja , Omesh Tickoo

Strong light-matter interactions facilitate not only emerging applications in quantum and non-linear optics but also modifications of materials properties. In particular the latter possibility has spurred the development of advanced…

Mesoscale and Nanoscale Physics · Physics 2021-08-17 Jakub Fojt , Tuomas P. Rossi , Tomasz J. Antosiewicz , Mikael Kuisma , Paul Erhart

Many drug delivery systems suffer from undesirable interactions with the host immune system. It has been experimentally established that covalent attachment (irreversible adsorption) of suitable macromolecules to the surface of the drug…

Biological Physics · Physics 2007-05-23 Radek Erban , Jonathan Chapman , Kerry D. Fisher , Ioannis G. Kevrekidis , Leonard W. Seymour

We consider the model of random sequential adsorption, with depositing objects, as well as those already at the surface, decreasing in size according to a specified time dependence, from a larger initial value to a finite value in the large…

Mathematical Physics · Physics 2010-10-12 Oleksandr Gromenko , Vladimir Privman

This work considers the problem of learning the structure of multivariate linear tree models, which include a variety of directed tree graphical models with continuous, discrete, and mixed latent variables such as linear-Gaussian models,…

Machine Learning · Computer Science 2011-11-09 Animashree Anandkumar , Kamalika Chaudhuri , Daniel Hsu , Sham M. Kakade , Le Song , Tong Zhang

We apply the recently developed triangular tessellation technique as presented in [J. de Graaf et al., Phys. Rev. E 80, 051405 (2009)] to calculate the free energy associated with the adsorption of anisotropic colloidal particles at a flat…

Soft Condensed Matter · Physics 2015-05-18 J. de Graaf , M. Dijkstra , R. van Roij

Background: In clinical research, the Bland-Altman analysis is commonly used to assess agreement of metric measurements made by two or more techniques, devices or methods. The approach can also deal with repeated measurements per subject or…

Efficient sampling from constraint manifolds, and thereby generating a diverse set of solutions for feasibility problems, is a fundamental challenge. We consider the case where a problem is factored, that is, the underlying nonlinear…

Robotics · Computer Science 2021-03-30 Joaquim Ortiz-Haro , Valentin N. Hartmann , Ozgur S. Oguz , Marc Toussaint

We consider the problem of modeling discrete-valued vector time series data using extensions of Chow-Liu tree models to capture both dependencies across time and dependencies across variables. Conditional Chow-Liu tree models are…

Machine Learning · Computer Science 2012-07-19 Sergey Kirshner , Padhraic Smyth , Andrew Robertson