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Understanding the structure of supramolecular complexes provides insight into their functional capabilities and how they can be modulated in the context of disease. Super-resolution microscopy (SRM) excels in performing this task by…

Quantitative Methods · Quantitative Biology 2023-08-09 Afonso Mendes , Hannah S. Heil , Simao Coelho , Christophe Leterrier , Ricardo Henriques

The Minimum Set Cover Problem (MSCP) is a classical NP-hard combinatorial optimization problem with numerous applications in science and engineering. Although a wide range of exact, approximate, and metaheuristic approaches have been…

Artificial Intelligence · Computer Science 2026-04-07 Isidora Hernández , Héctor Ferrada , Cristóbal A. Navarro

The Intrinsic Surface Finite Element Method (ISFEM) was recently proposed to solve Partial Differential Equations (PDEs) on surfaces. ISFEM proceeds by writing the PDE with respect to a local coordinate system anchored to the surface and…

Numerical Analysis · Mathematics 2024-10-08 Elena Bachini , Mario Putti

Automatic detection and segmentation of overlapping leaves in dense foliage can be a difficult task, particularly for leaves with strong textures and high occlusions. We present Dense-Leaves, an image dataset with ground truth segmentation…

Computer Vision and Pattern Recognition · Computer Science 2018-04-06 Daniel D. Morris

Electronic structure simulation (ESS) has been used for decades to provide quantitative scientific insights on an atomistic scale, enabling advances in chemistry, biology, and materials science, among other disciplines. Following standard…

Machine Learning · Computer Science 2024-06-06 Hatem Helal , Andrew Fitzgibbon

A mathematical programming problem with affine equilibrium constraints (AMPEC) is a bilevel programming problem where the lower one is a parametric affine variational inequality. We formulate some classes of bilevel programming in forms of…

Optimization and Control · Mathematics 2011-05-18 Le Dung Muu , Tran Dinh Quoc , Le Thi Hoai An , Pham Dinh Tao

We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's possible to train ML models to predict materials…

We present SQUEzE, a software package to classify quasar spectra and estimate their redshifts. SQUEzE is a random forest classifier operating on the parameters of candidate emission peaks identified in the spectra. We test the performance…

Astrophysics of Galaxies · Physics 2020-07-01 Ignasi Pérez-Ràfols , Matthew M. Pieri , Michael Blomqvist , Sean Morrison , Debopam Som

Decision trees and random forest remain highly competitive for classification on medium-sized, standard datasets due to their robustness, minimal preprocessing requirements, and interpretability. However, a single tree suffers from high…

Machine Learning · Statistics 2025-12-02 Cencheng Shen , Yuexiao Dong , Carey E. Priebe

We assume that the scale of the soft supersymmetry breaking masses, m_SUSY, sliding at tree level, is fixed by the minimization of the potential, but without a significant contribution of the cosmological term. Under these assumptions the…

High Energy Physics - Phenomenology · Physics 2009-10-09 Riccardo Barbieri , Alessandro Strumia

We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to…

Chemical Physics · Physics 2018-08-20 Pavlo O. Dral , Alec Owens , Sergei N. Yurchenko , Walter Thiel

MEASP is a multi-engine solver for ground ASP programs. It exploits algorithm selection techniques based on classification to select one among a set of out-of-the-box heterogeneous ASP solvers used as black-box engines. In this paper we…

Artificial Intelligence · Computer Science 2014-05-06 Marco Maratea , Luca Pulina , Francesco Ricca

This work presents a microscale approach for simulating the dielectrophoresis (DEP) assembly of polarizable particles under an external electric field. The model is shown to capture interesting dynamical and topological features, such as…

Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set…

Statistics Theory · Mathematics 2014-11-05 Peter Binev , Albert Cohen , Wolfgang Dahmen , Ronald DeVore

Shapley-related techniques have gained attention as both global and local interpretation tools because of their desirable properties. However, their computation using conditional expectations is computationally expensive. Approximation…

Machine Learning · Statistics 2022-07-13 Zhipu Zhou , Jie Chen , Linwei Hu

The one-dimensional asymmetric simple exclusion process (ASEP), where $N$ hard-core particles hop forward with rate $1$ and backward with rate $q<1$, is considered on a periodic lattice of $L$ site. Using KPZ universality and previous…

Statistical Mechanics · Physics 2016-10-19 Sylvain Prolhac

The process of protein synthesis in biological systems resembles a one dimensional driven lattice gas in which the particles have spatial extent, covering more than one lattice site. We expand the well studied Totally Asymmetric Exclusion…

Statistical Mechanics · Physics 2009-11-10 Leah B. Shaw , R. K. P. Zia , Kelvin H. Lee

Currently available experimental data from electroweak precision observables (EWPO), B-physics observables (BPO) and cosmological data can be combined to extract the preferred value of SUSY mass scales. We review recent results on the…

High Energy Physics - Phenomenology · Physics 2009-02-02 S. Heinemeyer

The algorithm "automated compression of environments" (ACE) [Nat. Phys. 18, 662 (2022)] provides a versatile way of simulating an extremely broad class of open quantum systems. This is achieved by encapsulating the influence of the…

Quantum Physics · Physics 2025-05-01 Moritz Cygorek , Brendon W. Lovett , Jonathan Keeling , Erik M. Gauger

The notion of software entropy is often invoked to describe the tendency of software systems to become increasingly disordered as they evolve, yet existing approaches to quantify it are largely heuristic. In this work we introduce a formal…

Software Engineering · Computer Science 2026-03-24 Jerónimo Fotinós , Juan B. Cabral