Convolution kernel of size 5 with arbitrary shape. by Xinwei Wang (352488)

Arbitrary Design of DNA-Programmable 3D Crystals through Symmetry Mapping by Jason S. Kahn (2744830)

Supplementary file 1_Optimizing quantum convolutional neural network architectures for arbitrary data dimension.pdf by Changwon Lee (20812727)

“…The number of input qubits determines the dimensions (i.e., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”

Summary of key parameters used in the CSCAP algorithm. by Manxing Shi (22367181)

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Efficient Sampling From the Watson Distribution in Arbitrary Dimensions by Lukas Sablica (19933752)

“…<p>In this article, we present two efficient methods for sampling from the Watson distribution in arbitrary dimensions. …”

Classification of PavCA Index scores with the k-Means algorithm where k = 3. by Camille Godin (21445879)

The proposed adaptive clustering algorithm determines the optimal distance parameters for two lightning events, <i>p</i>₁ and <i>p</i>₂. by Manxing Shi (22367181)

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Two representative subsets of (A) high-flash-rate and (B) low-flash-rate lightning data identified by the CC3D algorithm. by Manxing Shi (22367181)

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EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…In medicinal chemistry, they are the basis for analyzing ligand–biomacromolecule interactions. Ertl’s algorithm is an approach to extract functional groups in arbitrary organic molecules that does not depend on predefined libraries of functional groups. …”

Summary of greedy algorithms presented in this section. Details of approximation factors for FastGreedy and UnitGreedy may be found in [26] and [25], respectively. by Jeffrey Keithley (14626551)

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Thunderstorm clouds were identified and extracted by the CSCAP algorithm from 0000–0600 BJT (Beijing Time) on 29 May 2015. by Manxing Shi (22367181)

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, SingletonGreedy, FastGreedy and baselines for = 0.535 in Iowa for FRED (first column) and SafeGraph (second col... by Jeffrey Keithley (14626551)

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Metapopulation model notation. by Jeffrey Keithley (14626551)

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Estimates of for each problem instance. by Jeffrey Keithley (14626551)

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The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, FastGreedy and baselines for = 0.525 in Texas for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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Approximation factors for each problem instance. by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by all approaches for = 0.5345 in New Hampshire for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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FastGreedy, UnitGreedy, SingletonGreedy, 3-EnumGreedy, and POMS comparison with respect to practical running time (estimated for POMS) to achieve approximation guarantee for New Ha... by Jeffrey Keithley (14626551)

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Distribution of (A) temporal difference set (DistT) and (B) spatial distance set (DistS) values by sample number, for the lightning data subset (Fig 3(B)) identified by the CC3D al... by Manxing Shi (22367181)

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