Energy minimization
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Saliency-Aware Video Object Segmentation Open
Video saliency, aiming for estimation of a single dominant object in a sequence, offers strong object-level cues for unsupervised video object segmentation. In this paper, we present a geodesic distance based technique that provides reliab…
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3Drefine: an interactive web server for efficient protein structure refinement Open
3Drefine is an interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative o…
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Large deformations of planar extensible beams and pantographic lattices: heuristic homogenization, experimental and numerical examples of equilibrium Open
The aim of this paper is to find a computationally efficient and predictive model for the class of systems that we call ‘pantographic structures’. The interest in these materials was increased by the possibilities opened by the diffusion o…
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Energy Efficient UAV Communication With Energy Harvesting Open
This paper investigates an unmanned aerial vehicle (UAV)-enabled wireless communication system with energy harvesting, where the UAV transfers energy to the users in half duplex or full duplex, and the users harvest energy for data transmi…
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Unsupervised Single Image Dehazing Using Dark Channel Prior Loss Open
Single image dehazing is a critical stage in many modern-day autonomous vision applications. Early prior-based methods often involved a time-consuming minimization of a hand-crafted energy function. Recent learning-based approaches utilize…
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Completing density functional theory by machine learning hidden messages from molecules Open
Kohn–Sham density functional theory (DFT) is the basis of modern computational approaches to electronic structures. Their accuracy heavily relies on the exchange-correlation energy functional, which encapsulates electron–electron interacti…
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The Quantum Approximate Optimization Algorithm and the Sherrington-Kirkpatrick Model at Infinite Size Open
The Quantum Approximate Optimization Algorithm (QAOA) is a general-purpose algorithm for combinatorial optimization problems whose performance can only improve with the number of layers . While QAOA holds promise as an algorithm that can b…
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Three-Dimensional-Printed Multistable Mechanical Metamaterials With a Deterministic Deformation Sequence Open
Multistable mechanical metamaterials are materials that have multiple stable configurations. The geometrical changes caused by the transition of the metamaterial from one stable state to another, could be exploited to obtain multifunctiona…
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Symmetric and asymmetric tilt grain boundary structure and energy in Cu and Al (and transferability to other fcc metals) Open
Symmetric and asymmetric tilt grain boundaries in Cu and Al were generated using molecular statics energy minimization in a classical molecular dynamics code with in-plane grain boundary translations and an atom deletion criterion. The fol…
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QuickFF: A program for a quick and easy derivation of force fields for metal‐organic frameworks from <i>ab initio</i> input Open
QuickFF is a software package to derive accurate force fields for isolated and complex molecular systems in a quick and easy manner. Apart from its general applicability, the program has been designed to generate force fields for metal‐org…
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MGM: A Significantly More Global Matching for Stereovision Open
International audience
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Road Damage Detection Based on Unsupervised Disparity Map Segmentation Open
This article presents a novel road damage detection algorithm based on unsupervised disparity map segmentation. Firstly, a disparity map is transformed by minimizing an energy function with respect to stereo rig roll angle and road dispari…
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The mixed deep energy method for resolving concentration features in\n finite strain hyperelasticity Open
The introduction of Physics-informed Neural Networks (PINNs) has led to an\nincreased interest in deep neural networks as universal approximators of PDEs\nin the solid mechanics community. Recently, the Deep Energy Method (DEM) has\nbeen p…
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Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling Open
Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of ab initio crystal structure prediction (CSP). One effective methodology for performing such a…
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Fusion-based Variational Image Dehazing Open
We propose a novel image-dehazing technique based on the minimization of two energy functionals and a fusion scheme to combine the output of both optimizations. The proposed fusion-based variational image-dehazing (FVID) method is a spatia…
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Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics Open
Identifying binding hotspots on protein surfaces is of prime interest in structure-based drug discovery, either to assess the tractability of pursuing a protein target or to drive improved potency of lead compounds. Computational approache…
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Improved protein structure prediction using predicted inter-residue orientations Open
The prediction of inter-residue contacts and distances from co-evolutionary data using deep learning has considerably advanced protein structure prediction. Here we build on these advances by developing a deep residual network for predicti…
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Coarse Trajectory Design for Energy Minimization in UAV-Enabled Open
This paper studies energy-efficient unmanned aerial vehicle (UAV)-enabled wireless communications, where the UAV acts as a flying base station (BS) to serve the ground users (GUs) within some predetermined latency constraints, e.g., reques…
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Wrapping of a spherical colloid by a fluid membrane Open
We theoretically study the elastic deformation of a fluid membrane induced by an adhering spherical colloidal particle within the framework of a Helfrich energy. Based on a full optimization of the membrane shape we find a continuous bindi…
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Efficient Resource Allocation for Mobile-Edge Computing Networks With NOMA: Completion Time and Energy Minimization Open
This paper investigates an uplink non-orthogonal multiple access (NOMA)-based mobile-edge computing (MEC) network. Our objective is to minimize a linear combination of the completion time of all users' tasks and the total energy consumptio…
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Attribute2Image: Conditional Image Generation from Visual Attributes Open
This paper investigates a novel problem of generating images from visual attributes. We model the image as a composite of foreground and background and develop a layered generative model with disentangled latent variables that can be learn…
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Geometric optimization via composite majorization Open
Many algorithms on meshes require the minimization of composite objectives, i.e. , energies that are compositions of simpler parts. Canonical examples include mesh parameterization and deformation. We propose a second order optimization ap…
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Machine Learning Approaches toward Orbital-free Density Functional Theory: Simultaneous Training on the Kinetic Energy Density Functional and Its Functional Derivative Open
Orbital-free approaches might offer a way to boost the applicability of density functional theory by orders of magnitude in system size. An important ingredient for this endeavor is the kinetic energy density functional. Snyder et al. [ Ph…
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Operation of the Multiple Energy System with Optimal Coordination of the Consumers in Energy Market Open
In this paper, optimal coordination of the demand side under uncertainty of the energy price in energy market is studied. The consumers by demand response programs (DRPs) have optimal role in minimization of the energy generation costs in …
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Energy Minimization in RIS-Assisted UAV-Enabled Wireless Power Transfer Systems Open
Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) systems\noffer significant advantages in coverage and deployment flexibility, but suffer\nfrom endurance limitations due to the limited onboard energy. This paper\npropose…
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Interactive Cosegmentation Using Global and Local Energy Optimization Open
We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles t…
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Higher Order Energies for Image Segmentation Open
A novel energy minimization method for general higher order binary energy functions is proposed in this paper. We first relax a discrete higher order function to a continuous one, and use the Taylor expansion to obtain an approximate lower…
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NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems Open
Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials, or separations problems. In this paper, a novel algorithm has been developed for the global …
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Self-Assembly of Cubes into 2D Hexagonal and Honeycomb Lattices by Hexapolar Capillary Interactions Open
Particles adsorbed at a fluid-fluid interface induce capillary deformations that determine their orientations and generate mutual capillary interactions which drive them to assemble into 2D ordered structures. We numerically calculate, by …
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Protein homology model refinement by large-scale energy optimization Open
Significance Protein structure refinement by direct global energy optimization has been a longstanding challenge in computational structural biology due to limitations in both energy function accuracy and conformational sampling. This manu…