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Many real world systems need to operate on heterogeneous information networks that consist of numerous interacting components of different types. Examples include systems that perform data analysis on biological information networks; social…

Artificial Intelligence · Computer Science 2017-07-26 Parisa Kordjamshidi , Sameer Singh , Daniel Khashabi , Christos Christodoulopoulos , Mark Summons , Saurabh Sinha , Dan Roth

A bicategory approach to differential cohomology is presented. Based on the axioms of Bunke-Schick, a symmetric monoidal groupoid is associated to differential refinements of cohomology theories. It is proven that such differential…

Algebraic Topology · Mathematics 2013-03-01 Markus Upmeier

Perturbation experiments allow biologists to discover causal relationships between variables of interest, but the sparsity and high dimensionality of these data pose significant challenges for causal structure learning algorithms.…

Quantitative Methods · Quantitative Biology 2024-10-21 Peiwen Li , Menghua Wu

Numerous methods have been proposed to transform color and grayscale images to their single bit-per-pixel binary counterparts. Commonly, the goal is to enhance specific attributes of the original image to make it more amenable for analysis.…

Computer Vision and Pattern Recognition · Computer Science 2021-05-06 Shumeet Baluja

Graphs are ubiquitous data structures for representing interactions between entities. With an emphasis on the use of graphs to represent chemical molecules, we explore the task of learning to generate graphs that conform to a distribution…

Machine Learning · Computer Science 2019-03-08 Qi Liu , Miltiadis Allamanis , Marc Brockschmidt , Alexander L. Gaunt

As evidenced by various recent and significant papers within the frequentist literature, along with numerous applications in macroeconomics, genomics, and neuroscience, there continues to be substantial interest to understand the…

Methodology · Statistics 2019-06-13 Jonathan P Williams , Yuying Xie , Jan Hannig

Graph-based reaction systems were recently introduced as a generalization of the intensely studied set-based reaction systems. They deal with simple edge-labeled directed graphs, and dynamic semantics of graph-based reaction systems is…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-04 Hans-Jörg Kreowski , Aaron Lye

The criteria for determining graph isomorphism are crucial for solving graph isomorphism problems. The necessary condition is that two isomorphic graphs possess invariants, but their function can only be used to filtrate and subdivide…

Graphics · Computer Science 2025-08-19 Chuanfu Hu , Aimin Hou

We define refined invariants which "count" nodal curves in sufficiently ample linear systems on surfaces, conjecture that their generating function is multiplicative, and conjecture explicit formulas in the case of K3 and abelian surfaces.…

Algebraic Geometry · Mathematics 2015-09-01 Lothar Göttsche , Vivek Shende

Generating realistic graph-structured data is challenging due to discrete connectivity, varying graph sizes, and class-specific structural patterns. Recent Generative Adversarial Networks (GAN)-based graph generation methods improve edge…

Machine Learning · Computer Science 2026-05-29 James Sargant , Seyedeh Ava Razi Razavi , Renata Dividino , Sheridan Houghten

We present an adaptive refinement algorithm for T-splines on unstructured 2D meshes. While for structured 2D meshes, one can refine elements alternatingly in horizontal and vertical direction, such an approach cannot be generalized directly…

Numerical Analysis · Mathematics 2022-05-03 Roland Maier , Philipp Morgenstern , Thomas Takacs

The (gradient-based) bilevel programming framework is widely used in hyperparameter optimization and has achieved excellent performance empirically. Previous theoretical work mainly focuses on its optimization properties, while leaving the…

Machine Learning · Computer Science 2021-10-26 Fan Bao , Guoqiang Wu , Chongxuan Li , Jun Zhu , Bo Zhang

This work is concerned with the convex analysis of functions defined on (not necessarily finite-dimensional) Hilbert spaces whose values depend solely on a certain ``spectrum'' of the arguments, a class we term ``spectral functions.'' We…

Optimization and Control · Mathematics 2026-03-11 Hòa T. Bùi , Minh N. Bùi , Christian Clason

For many practical problems, the regression models follow the strong heredity property (also known as the marginality), which means they include parent main effects when a second-order effect is present. Existing methods rely mostly on…

Methodology · Statistics 2020-07-28 Kedong Chen , William Li , Sijian Wang

We advocate the use of qualitative models in the analysis of large biological systems. We show how qualitative models are linked to theoretical differential models and practical graphical models of biological networks. A new technique for…

Molecular Networks · Quantitative Biology 2007-05-23 Philippe Veber , Michel Le_Borgne , Anne Siegel , Sandrine Lagarrigue , Ovidiu Radulescu

We in this paper propose a directional regression based approach for ultrahigh dimensional sufficient variable screening with censored responses. The new method is designed in a model-free manner and thus can be adapted to various complex…

Methodology · Statistics 2018-02-28 Menghao Xu , Zhou Yu , Jun Shao

Hierarchical transition systems provide a popular mathematical structure to represent state-based software applications in which different layers of abstraction are represented by inter-related state machines. The decomposition of high…

Logic in Computer Science · Computer Science 2016-06-08 Alexandre Madeira , Manuel A. Martins , Luís S. Barbosa

Point-based interactive image segmentation can ease the burden of mask annotation in applications such as semantic segmentation and image editing. However, fully extracting the target mask with limited user inputs remains challenging. We…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Chaowei Fang , Ziyin Zhou , Junye Chen , Hanjing Su , Qingyao Wu , Guanbin Li

Graphs are a fundamental abstraction for modeling relational data. However, graphs are discrete and combinatorial in nature, and learning representations suitable for machine learning tasks poses statistical and computational challenges. In…

Machine Learning · Statistics 2019-05-16 Aditya Grover , Aaron Zweig , Stefano Ermon

We analyze the response of bilayer graphene to an external transverse electric field using a variational method. A previous attempt to do so in a recent paper by Falkovsky [Phys. Rev. B 80, 113413 (2009)] is shown to be flawed. Our…

Mesoscale and Nanoscale Physics · Physics 2011-08-17 M. M. Fogler , E. McCann