Results 21 to 30 of about 62,890 (222)
Variational approach to relaxed topological optimization: closed form solutions for structural problems in a sequential pseudo-time framework [PDF]
, 2019 The work explores a specific scenario for structural computational optimization based on the following elements: (a) a relaxed optimization setting considering the ersatz (bi-material) approximation, (b) a treatment based on a non-smoothed characteristic
Cante Terán, Juan Carlos +3 more
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IEEE Access, 2019 Although the hybrid analog–digital processing reduces the hardware complexity to realize massive multiple-input multiple-output system, it increases the difficulty of channel estimation significantly since the base station cannot obtain enough ...
Yurong Wang +3 more
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Single-step deep reinforcement learning for two- and three-dimensional optimal shape design
AIP Advances, 2022 This research gauges the capabilities of deep reinforcement learning (DRL) techniques for direct optimal shape design in computational fluid dynamics (CFD) systems.
H. Ghraieb +4 more
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Optimal micropatterns in 2D transport networks and their relation to image inpainting
, 2016 We consider two different variational models of transport networks, the so-called branched transport problem and the urban planning problem. Based on a novel relation to Mumford-Shah image inpainting and techniques developed in that field, we show for a ...
Brancolini, Alessio +2 more
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Differentiable Programming Tensor Networks
Physical Review X, 2019 Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and optimizes them using gradient search. The concept emerges from deep learning but is not limited to training neural networks. We present the
Hai-Jun Liao +3 more
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IEEE Photonics Journal, 2016 In this paper, we propose a new $\ell _{0}$ -regularized approach to remove the temperature-dependent nonuniformity effects induced by the infrared (IR) imaging optics in an aerothermal environment.
Li Liu, Tianxu Zhang
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Variational matrix product state approach to quantum impurity models [PDF]
, 2008 We present a unified framework for renormalization group methods, including Wilson's numerical renormalization group (NRG) and White's density-matrix renormalization group (DMRG), within the language of matrix product states.
Cirac, J. I. +4 more
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise
IEEE Transactions on Quantum EngineeringGiven their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge.
Zichang He +3 more
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Variational Monte Carlo with the Multi-Scale Entanglement Renormalization Ansatz [PDF]
, 2012 Monte Carlo sampling techniques have been proposed as a strategy to reduce the computational cost of contractions in tensor network approaches to solving many-body systems.
Ferris, Andrew J., Vidal, Guifre
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Discrete mechanics and optimal control: An analysis [PDF]
, 2009 The optimal control of a mechanical system is of crucial importance in many application areas. Typical examples are the determination of a time-minimal path in vehicle dynamics, a minimal energy trajectory in space mission design, or optimal motion ...
Junge, Oliver +2 more
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