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Phylogenetic graph models beyond trees

DISCRETE APPLIED MATHEMATICS 2009年第10期157卷 2361-2369页

作者： Brandes, Ulrik Cornelsen, Sabine Univ Konstanz Dept Comp & Informat Sci D-78457 Constance Germany

A graph model for a set (sic) of splits of a set X consists of a graph and a map from X to the vertices of the graph such that the inclusion-minimal cuts of the graph represent (sic). Phylogenetic trees are graph models in which the graph is a tree. We show that the model can be generalized to a cactus (i.e. a tree of edges and cycles) without losing computational efficiency. A cactus can represent a quadratic rather than linear number of splits in linear space. We show how to decide in linear time in the size of a succinct representation of (sic) whether a set of splits has a cactus model, and if so construct it within the same time bounds. As a byproduct, we show how to construct the subset of all compatible splits and a maximal compatible set of splits in linear time. Note that it is N P-complete to find a compatible subset of maximum size. Finally, we briefly discuss further generalizations of tree models. (c) 2008 Elsevier B.V. All rights reserved.

关键词： Phylogenetic trees graph models Splits Compatibility Cactus model

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The Infinity Mirror Test for graph models

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2023年第4期35卷 4281-4292页

作者： Sikdar, Satyaki Cedre, Daniel Gonzalez Ford, Trenton W. Weninger, Tim Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

graph models, like other machine learning models, have implicit and explicit biases built-in, which often impact performance in nontrivial ways. The model's faithfulness is often measured by comparing the newly generated graph against the source graph using any number of graph properties. Therefore, differences in the size or topology of the generated graph indicate a loss in the model. Yet, in many systems, errors encoded in loss functions are subtle and not well understood. In the present work, we introduce the Infinity Mirror test for analyzing the robustness of graph models. This straightforward stress test works by repeatedly fitting a model to its outputs. A hypothetically perfect graph model would have no deviation from the source graph;however, a model's implicit biases and assumptions are exaggerated by the Infinity Mirror test, exposing potential previously obscured issues. Through an analysis of thousands of experiments on synthetic and real-world graphs, we show that several conventional graph models degenerate in exciting and informative ways. We believe that the observed degenerative patterns are clues to the future development of better graph models.

关键词： Mirrors Measurement Predictive models Computational modeling Data models Analytical models Feature extraction graph models methodology biases

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graph models For Social Relations

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Electronic Notes in Discrete Mathematics 2009年第C期33卷 101-108页

作者： Yegnanarayanan, V. UmaMaheswari, G.K. Department of Computer Applications DMI college of engineering Palanchur Chennai 602103 Nazarathpet Post India Research and Development Centre Bharathiar University Coimbatore 641046 India

The study of social networks by anthropologists has been based on the basic notions of graph theory, as has the identification and analysis of social cliques. There is little consensus among mathematicians about terminology, and social scientists have drawn fortuitously on various mathematical vocabularies as well as inventing their own technical terms. This paper deals with the effectiveness of graph models to model social relationship and the related intricacies. © 2009 Elsevier B.V. All rights reserved.

关键词： Algebraic models Anthropology graph models

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Optimization and Complexity Reduction of Switch-Reconfigured Antennas Using graph models

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2009年 8卷 1072-1075页

作者： Costantine, Joseph Christodoulou, Christos G. Abdallah, Chaouki T. Barbin, Silvio E. Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA Univ Sao Paulo BR-05508900 Sao Paulo Brazil Brazilian Govt Renato Archer Dept Sci & Technol Ctr Informat Technol BR-13069901 Campinas SP Brazil

This letter addresses the optimization and complexity reduction of switch-reconfigured antennas. A new optimization technique based on graph models is investigated. This technique is used to minimize the redundancy in a reconfigurable antenna structure and reduce its complexity. A graph modeling rule for switch-reconfigured antennas is proposed, and examples are presented.

关键词： Complexity graph models optimization reconfigurable antennas switches

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The Analysis of a Reconfigurable Antenna With a Rotating Feed Using graph models

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2009年 8卷 943-946页

作者： Costantine, Joseph Al-Saffar, Sinan Christodoulou, Christos G. Kabalan, Karim Y. El-Hajj, Ali Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA Amer Univ Beirut Dept Elect & Comp Engn Beirut 11072020 Lebanon

This letter investigates a new reconfigurable antenna technique based on the rotation of a slot. The surface currents are redistributed for each slot position. The antenna is simulated, fabricated, and tested. The return loss frequency tuning matches the simulated data. The antenna radiation pattern remains unchanged for different slot positions. Finally, the process for automatic rotation and control of the slot is investigated using graph models.

关键词： graph models microstrip antennas reconfigurable antennas

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Robustness of MetaNet graph models: Predicting control of urea production in humans

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BIOSYSTEMS 2002年第1期65卷 61-78页

作者： Kohn, MC Tohmaz, AS Giroux, KJ Blumenthal, GM Feezor, MD Millington, DS NIEHS Lab Computat Biol & Risk Anal Res Triangle Pk NC 27709 USA BioKinet Inc Res Triangle Pk NC 27709 USA Duke Univ Med Ctr Med Genet Program Inst Mass Spectrometry Res Triangle Pk NC 27709 USA

Urea production in human liver was described by a MetaNet graph, a flowchart-like representation of metabolic pathways that includes parameters for the kinetic constants of the constituent enzymes. Formal operations on the graph facilitate the identification of ligand-binding equilibria that participate in feedback regulation in the network of biochemical reactions. The state of the biochemical network is specified by the concentrations of the intermediates. At any particular time, the influence of an identified locus of regulation is proportional to the respective fractional saturation of the corresponding binding site. Enzymes that make or consume the feedback chemicals share in the control of the strength of the feedback signal in proportion to their fractional saturation. This model predicts control of urea production by the processes that deliver amino groups to the urea cycle enzymes more than by the cycle enzymes themselves. Mitochondrial membrane transport processes are important for transmission of information through the network, but irreversible enzymes and processes far from equilibrium control the strength of the feedback signal. Systematic variation of the parameter values by amounts comparable to the expected variability of their measured values indicated a high probability of invariance in the identities of the predicted control points. The properties of the model are consistent with those of error-tolerant scale-free networks. These results demonstrate the robustness of a MetaNet model's predictions with respect to uncertainties in the values of its parameters. Published by Elsevier Science Ireland Ltd.

关键词： graph models robustness metabolic regulation urea cycle

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Easiness in graph models

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THEORETICAL COMPUTER SCIENCE 2006年第1期354卷 4-23页

作者： Berline, C Salibra, A CNRS F-72251 Paris 05 France Univ Paris 07 F-72251 Paris 05 France Univ Ca Foscari Venezia Dipartimento Informat I-30172 Venice Italy

We generalize Baeten and Boerboom's method of forcing to show that there is a fixed sequence (u(k))(k is an element of omega) of closed (untyped) lambda-terms satisfying the following properties: (a) For any countable sequence (g(k))(k is an element of omega) of Scott continuous functions (of arbitrary arity) on the power set of an arbitrary countable set, there is a graph model such that (lambda ***)(lambda ***)u(k) represents g(k) in the model. (b) For any countable sequence (t(k))(k is an element of omega) of Closed -terms there is a graph model that satisfies (lambda ***)(lambda ***)u(k) for all k. We apply these two results, which are corollaries of a unique theorem, to prove the existence of (1) a finitely axiomatized lambda-theory L such that the interval lattice constituted by the lambda-theories extending L is distributive;(2) a continuum of pairwise inconsistent graph theories (= lambda-theories that can be realized as theories of graph models);(3) a congruence distributive variety of combinatory algebras (lambda abstraction algebras, respectively). (c) 2005 Elsevier B.V. All rights reserved.

关键词： untyped lambda-calculus graph models easy terms Scott's continuous semantics lattice of lambda-theories webbed models combinatory algebras lambda abstraction algebras

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Exploiting Semantic Structured Relationships Using graph models for Semantic Annotations 10

Exploiting Semantic Structured Relationships Using Graph Mod...

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10th International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Fan, Yuhua Fan, Liya Liaocheng Univ Sch Math Sci Liaocheng Shandong Peoples R China

ISBN: (纸本)9781538693896

This paper proposes a novel and efficient approach to exploit semantic relationships using semantic modeling for semantic annotation tasks. The existing methods learn knowledge of concepts and their relationships based on context cues. Starting with a large set of objects detectors, the proposed method refines the initial annotation results using the learned semantic relationships, which can preserve the consistency and effective of the annotation over a semantic graph. Different from the existing graph learning methods which capture relations among data instances, the semantic graphs treat concepts as nodes and concept affinities as the weights of edges. Particularly, the proposed method can not only learn the semantic cues effectively through the semantic graph models to improve the annotation results, but also can adapt the concept affinities to unseen images. The method provides a means to handle structured relationship change between training and test data, which occurs very often in semantic annotation tasks. Our experiments on NYUv2 demonstrate that the proposed approach outperform the state-of-the-art algorithms.

关键词： Semantic annotation visual relationship detection graph models

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ASSESSING graph models FOR DESCRIPTION OF BRAIN NETWORKS

ASSESSING GRAPH MODELS FOR DESCRIPTION OF BRAIN NETWORKS

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8th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro

作者： Yuan, Yixuan Guo, Lei Lv, Peili Hu, Xintao Zhang, Degang Han, Junwei Xie, Li Liu, Tianming Northwest Polytech Univ Sch Automat Xian 710072 Peoples R China Univ Georgia Dept Comp Sci & Bioimaging Res Ctr Athens GA 30602 USA Zhejiang Univ Dept Informat Sci & Elect Engn Hangzhou Peoples R China

ISBN: (纸本)9781424441280

Both structural and functional brain networks have been investigated in the literature with enthusiasm via graph-theoretical methods. However, an important issue that has not been adequately addressed before is: what is the optimal graph model for describing brain networks, both in structural and functional aspects? We address this question in the following three aspects. First, multi-resolution structural brain networks are reconstructed via cortical surface parcellation based on white matter fiber density information. Second, the global and local graph properties of the constructed networks are measured using state-of-the-art graph analysis algorithms and tools, and are further compared with five popular random graph models. Third, a functional simulation study is conducted to evaluate the synchronizability of the five models. Our results suggest that the STICKY graph model fits brain networks the best in terms of global and local graph properties, and the fastest speed of functional synchronization.

关键词： multi-resolution structural brain networks graph models graph properties

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Altgraph: Redesigning Quantum Circuits Using Generative graph models for Efficient Optimization 24

AltGraph: Redesigning Quantum Circuits Using Generative Grap...

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34th Great Lakes Symposium on VLSI (GLSVLSI)

作者： Beaudoin, Collin Phalak, Koustubh Ghosh, Swaroop Penn State Univ University Pk PA 16802 USA

ISBN: (纸本)9798400706059

Quantum circuit transformation aims to optimize circuits for depth, gate count, and compatibility with Noisy Intermediate Scale Quantum (NISQ) devices that suffer from various error sources. Prior methods use combinations of expert-defined rules and Reinforcement Learning (RL). We introduce Altgraph, a novel approach employing generative graph models to generate functionally equivalent quantum circuits using-specifically, Direct Acyclic graph (DAG) Variational Autoencoder (D-VAE) variants (GRU and GCN) and Deep Generative Model for graphs (DeepGMG). Altgraph perturbs the latent space to generate quantum circuits optimized for hardware coupling maps, reducing gate count by 37.55% and circuit depth by 37.75% post-transpiling, with 0.0074 Mean Squared Error (MSE) in the density matrix-outperforming state-of-the-art methods by 2.56%.

关键词： Circuit transformation graph models DAG generation

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