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Competing strategies in an evolutionary game model, or species in a biosystem, can easily form a larger unit which protects them from the invasion of an external actor. Such a defensive alliance may have two, three, four or even more…

Physics and Society · Physics 2023-06-21 Attila Szolnoki , Xiaojie Chen

The field theory of nonrelativistic fermions interacting via contact interactions can be used to calculate the properties of few-body systems of cold atoms confined in harmonic traps. The state-operator correspondence of Non-Relativistic…

Other Condensed Matter · Physics 2009-11-13 Thomas Mehen

This paper presents a convexity analysis for the dynamic snake model based on the Potential Energy functional and the Hamiltonian formulation of the classical mechanics. First we see the snake model as a dynamical system whose singular…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Gilson Antonio Giraldi , Antonio Alberto Fernandes de Oliveira

Bayesian approaches to data analysis and machine learning are widespread and popular as they provide intuitive yet rigorous axioms for learning from data; see Bernardo and Smith (2004) and Bishop (2006). However, this rigour comes with a…

Methodology · Statistics 2017-01-31 Chris Holmes , Stephen Walker

Simple tree models for articulated objects prevails in the last decade. However, it is also believed that these simple tree models are not capable of capturing large variations in many scenarios, such as human pose estimation. This paper…

Computer Vision and Pattern Recognition · Computer Science 2013-05-13 Fang Wang , Yi Li

We present simulations of 2-d site animals on square and triangular lattices in non-trivial geomeLattice animals are one of the few critical models in statistical mechanics violating conformal invariance. We present here simulations of 2-d…

Statistical Mechanics · Physics 2009-11-10 Hsiao-Ping Hsu , Walter Nadler , Peter Grassberger

We study parameter estimation in Nonlinear Factor Analysis (NFA) where the generative model is parameterized by a deep neural network. Recent work has focused on learning such models using inference (or recognition) networks; we identify a…

Machine Learning · Statistics 2017-10-18 Rahul G. Krishnan , Dawen Liang , Matthew Hoffman

Ordinary differential equation models are nowadays widely used for the mechanistic description of biological processes and their temporal evolution. These models typically have many unknown and non-measurable parameters, which have to be…

Quantitative Methods · Quantitative Biology 2021-05-27 Alejandro F. Villaverde , Dilan Pathirana , Fabian Fröhlich , Jan Hasenauer , Julio R. Banga

To most applied statisticians, a fitting procedure's degrees of freedom is synonymous with its model complexity, or its capacity for overfitting to data. In particular, it is often used to parameterize the bias-variance tradeoff in model…

Other Statistics · Statistics 2017-01-06 Lucas Janson , William Fithian , Trevor Hastie

We describe an efficient theoretical criterion, suitable for indistinguishable particles to quantify the quantum correlations of any pure two-fermion state, based on the Slater rank concept. It represents the natural generalization of the…

Quantum Physics · Physics 2007-05-23 Fabrizio Buscemi , Paolo Bordone , Andrea Bertoni

Time-invariant linear dynamical system arises in many real-world applications,and its usefulness is widely acknowledged. A practical limitation with this model is that its latent dimension that has a large impact on the model capability…

Machine Learning · Computer Science 2019-06-25 Yang Li

We use the embedding formalism to construct conformal fields in $D$ dimensions, by restricting Lorentz-invariant ensembles of homogeneous neural networks in $(D+2)$ dimensions to the projective null cone. Conformal correlators may be…

High Energy Physics - Theory · Physics 2025-10-07 James Halverson , Joydeep Naskar , Jiahua Tian

In this paper, based on a fuzzy entropy feature selection framework, different methods have been implemented and compared to improve the key components of the framework. Those methods include the combinations of three ideal vector…

Machine Learning · Computer Science 2020-05-22 Zixiao Shen , Xin Chen , Jonathan M. Garibaldi

The capability of string theories to reproduce at low energy the observed pattern of quark and lepton masses and mixing angles is examined, focusing the attention on orbifold constructions, where the magnitude of Yukawa couplings depends on…

High Energy Physics - Theory · Physics 2009-10-22 J. A. Casas , F. Gómez , C. Muñoz

One of the problems in applying Genetic Algorithm is that there is some situation where the evolutionary process converges too fast to a solution which causes it to be trapped in local optima. To overcome this problem, a proper diversity in…

Neural and Evolutionary Computing · Computer Science 2011-09-02 Chaiwat Jassadapakorn , Prabhas Chongstitvatana

McNamara, Trimmer, and Houston (2012) claim to provide an explanation of certain systematic deviations from rational behavior using a mechanism that could arise through natural selection. We provide an arguably much simpler mechanism in…

Populations and Evolution · Quantitative Biology 2017-12-27 Joseph Y. Halpern , Lior Seeman

In this paper, new techniques that allow conditional entropy to estimate the combinatorics of symbols are applied to animal communication studies to estimate the communication's repertoire size. By using the conditional entropy estimates at…

Populations and Evolution · Quantitative Biology 2014-01-17 Reginald D. Smith

In this four-part prospectus, we first give a brief introduction to the motivation for studying entanglement entropy and some recent development. Then follows a summary of our recent work about entanglement entropy in states with…

Quantum Physics · Physics 2009-08-18 Wenxin Ding

We present a novel approach for estimating the 2D pose of an articulated object with an application to automated video analysis of small laboratory animals. We have found that deformable part models developed for humans, exemplified by the…

Computer Vision and Pattern Recognition · Computer Science 2018-06-29 Yuliang Guo , Lakshmi Narasimhan Govindarajan , Benjamin Kimia , Thomas Serre

How many parameters are required for a model to execute a given task? It has been argued that large language models, pre-trained via self-supervised learning, exhibit emergent capabilities such as multi-step reasoning as their number of…

Machine Learning · Computer Science 2024-09-23 Ingvar Ziemann , Nikolai Matni , George J. Pappas
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