Infusing theory into deep learning for interpretable reactivity prediction
Nature Communications, 2021 Machine learning faces challenges in catalyst design due to its black-box nature. Here, the authors develop a theory-infused neural network approach that integrates deep learning algorithms with the well-established d-band theory of chemisorption for ...
Shih-Han Wang +4 more
doaj +1 more source
Black-box optimization methods for hypersonic flow problems [PDF]
International Journal of Fluid EngineeringThis review examines the application of black-box optimization methods to hypersonic flow problems, with a particular emphasis on scenarios where computational fluid dynamics (CFD) simulations function as opaque, nontransparent models.
Davood Hoseinzade +2 more
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Efficient quantum gates and algorithms in an engineered optical lattice
Scientific Reports, 2021 In this work, trapped ultracold atoms are proposed as a platform for efficient quantum gate circuits and algorithms. We also develop and evaluate quantum algorithms, including those for the Simon problem and the black-box string-finding problem.
A. H. Homid +3 more
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Reproduction of Black-Box music analysis algorithms through machine learning [PDF]
, 2023 Eine Sammlung von semantischen Musik-Features (d.h. Metriken, die bestimmte Merkmale von Musikstücken quantifizieren), die vom Musik-Streaming-Dienst Spotify angeboten wird, zeigt wissenschaftliche Relevanz im Forschungsfeld Music Information Retrieval ...
Schmidt, Andreas
core +1 more source
The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms [PDF]
ITM Web of ConferencesMany global optimization problems are presented as a black-box model, in which there is no information on the objective function properties. Traditional optimization algorithms usually can't effectively solve that kind of problems.
Sopov Anton, Karaseva Tatiana
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Opening up the Black Box of Sensor Processing Algorithms through New Visualizations
Informatics, 2016 Vehicles and platforms with multiple sensors connect people in multiple roles with different responsibilities to scenes of interest. For many of these human–sensor systems there are a variety of algorithms that transform, select, and filter the sensor ...
Alexander M. Morison, David D. Woods
doaj +1 more source
Black-Box Algorithms for Sampling from Continuous Distributions
Proceedings of the 2006 Winter Simulation Conference, 2006 For generating non-uniform random variates, black-box algorithms are powerful tools that allow drawing samples from large classes of distri- butions. We give an overview of the design principles of such methods and show that they have advantages compared to specialized algorithms even for standard distributions, e.g., the marginal generation times are ...
Hörmann, Wolfgang, Leydold, Josef
openaire +6 more sources
Unknowing Algorithms: On Transparency of Unopenable Black Boxes
, 2017 published
Paßmann, Johannes, Boersma, Asher
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Black Box Algorithm Selection by Convolutional Neural Network [PDF]
, 2020 9 pages, 4 figures, 5 tables, journal ...
Yaodong He, Shiu Yin Yuen
openaire +4 more sources
AN ACTIVE-SET EVOLUTION STRATEGY FOR MIXED-INTEGER BLACK-BOX OPTIMIZATION WITH EXPLICIT CONSTRAINTS
, 2023 Many real-world applications involve the optimization of both continuous and discrete variables simultaneously. Evolution Strategies are stochastic black-box optimization techniques that are most commonly used for continuous optimization.
Hong, Yuan
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