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A promising approach to study condensed-matter systems is to simulate them on an engineered quantum platform. However, achieving the accuracy needed to outperform classical methods has been an outstanding challenge. Here, using eighteen…

Simulation and modeling are essential in product development, integrated into the design and manufacturing process to enhance efficiency and quality. They are typically represented as complex nonlinear differential algebraic equations. The…

Machine Learning · Computer Science 2026-03-25 Wenqiang Yang , Wenyuan Wu , Yong Feng , Changbo Chen

Many inference problems in structured prediction can be modeled as maximizing a score function on a space of labels, where graphs are a natural representation to decompose the total score into a sum of unary (nodes) and pairwise (edges)…

Machine Learning · Statistics 2021-02-19 Kevin Bello , Jean Honorio

Fractional polynomial models are potentially useful for response surfaces investigations. With the availability of routines for fitting nonlinear models in statistical packages they are increasingly being used. However, as in all…

Methodology · Statistics 2025-10-29 Luzia A. Trinca , Steven G. Gilmour

Considering the worst-case scenario, junction tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees. Unfortunately, its main tractability assumption requires the treewidth of a…

Discrete Mathematics · Computer Science 2022-02-10 Alexander Bauer , Shinichi Nakajima

We propose a novel methodology for discovering the presence of relationships realized as binary time series between variables in high dimension. To make it visually intuitive, we regard the existence of a relationship as an edge connection,…

Methodology · Statistics 2024-10-07 Masaki Toyoda , Yoshimasa Uematsu

A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions…

Molecular Networks · Quantitative Biology 2007-05-23 Bhaskar DasGupta , German Andres Enciso , Eduardo Sontag , Yi Zhang

The quality of numerical reconstructions for unknown parameters in inverse problems depends fundamentally on the selection of experimental data. To ensure a robust reconstruction, it is crucial to select data that are sensitive to the…

Numerical Analysis · Mathematics 2026-04-14 Kathrin Hellmuth , Christian Klingenberg , Qin Li

We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees…

Machine Learning · Statistics 2010-09-15 Myung Jin Choi , Vincent Y. F. Tan , Animashree Anandkumar , Alan S. Willsky

A challenge of molecular self-assembly is to understand how to design particles that self-assemble into a desired structure and not any of a potentially large number of undesired structures. Here we use simulation to show that a strategy of…

Statistical Mechanics · Physics 2017-02-27 Stephen Whitelam

Reconstructing continuous signals from a small number of discrete samples is a fundamental problem across science and engineering. In practice, we are often interested in signals with 'simple' Fourier structure, such as bandlimited,…

Data Structures and Algorithms · Computer Science 2018-12-24 Haim Avron , Michael Kapralov , Cameron Musco , Christopher Musco , Ameya Velingker , Amir Zandieh

Variability has always been a challenge to mitigate in electronics. This especially holds true for organic semiconductors, where reproducibility and long-term stability concerns hinder industrialization. By relying on a bio-inspired…

Emerging Technologies · Computer Science 2024-07-30 Scholaert Corentin , Coffinier Yannick , Pecqueur Sébastien , Alibart Fabien

This paper aims to maximize algebraic connectivity of networks via topology design under the presence of constraints and an adversary. We are concerned with three problems. First, we formulate the concave maximization topology design…

Optimization and Control · Mathematics 2017-11-15 Tor Anderson , Chin-Yao Chang , Sonia Martinez

The language of graph theory, or network science, has proven to be an exceptional tool for addressing myriad problems in neuroscience. Yet, the use of networks is predicated on a critical simplifying assumption: that the quintessential unit…

Neurons and Cognition · Quantitative Biology 2016-01-14 Chad Giusti , Robert Ghrist , Danielle S. Bassett

We consider ordered pairs $(X,\mathcal{B})$ where $X$ is a finite set of size $v$ and $\mathcal{B}$ is some collection of $k$-element subsets of $X$ such that every $t$-element subset of $X$ is contained in exactly $\lambda$ "blocks" $B\in…

Combinatorics · Mathematics 2018-03-14 William J. Martin , Douglas R. Stinson

Autonomous reconfiguration of agent-based systems is a key challenge in the study of programmable matter, distributed robotics, and molecular self-assembly. While substantial prior work has focused on size-preserving transformations, much…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-29 Nada Almalki , Siddharth Gupta , Othon Michail , Andreas Padalkin

Minimum storage regenerating codes have minimum storage of data in each node and therefore are maximal distance separable (MDS for short) codes. Thus, the number of nodes is upper bounded by $2^{\fb}$, where $\fb$ is the bits of data stored…

Information Theory · Computer Science 2017-10-06 Lingfei Jin , Yuan Luo , Chaoping Xing

We study the generalized minimum Manhattan network (GMMN) problem: given a set $P$ of pairs of two points in the Euclidean plane $\mathbb{R}^2$, we are required to find a minimum-length geometric network which consists of axis-aligned…

Data Structures and Algorithms · Computer Science 2020-04-28 Yuya Masumura , Taihei Oki , Yutaro Yamaguchi

This paper presents the novel `uniqueness tree' algorithm, as one possible method for determining whether two finite, undirected graphs are isomorphic. We prove that the algorithm has polynomial time complexity in the worst case, and that…

Discrete Mathematics · Computer Science 2016-06-22 Jonathan Gorard

We study experiment design for unique identification of the causal graph of a simple SCM, where the graph may contain cycles. The presence of cycles in the structure introduces major challenges for experiment design as, unlike acyclic…

Machine Learning · Computer Science 2023-12-15 Ehsan Mokhtarian , Saber Salehkaleybar , AmirEmad Ghassami , Negar Kiyavash