The G-clusteron requires the weight and location update rules to solve the XOR problem from arbitrary initial conditions. by Toviah Moldwin (10866708)

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

“…Through numerical simulations, we benchmarked the classification performance of various QCNN architectures across multiple datasets with arbitrary input data dimensions, including MNIST, Landsat satellite, Fashion-MNIST, and Ionosphere. …”

MTGSAM: Multiple-Trait Gibbs Sampler for Animal Models by Curtis P. Van Tassell (11666836)

“…<p>A set of FORTRAN programs to implement a multiple-trait Gibbs sampling algorithm for (co)variance component inference in animal models (MTGSAM) was developed. …”

Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets by Oscar M. Camacho (15360588)

“…For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localization rate in these studies. …”

Overview of data and command flow in our proposed system’s architecture. by Julian Bigge (22331861)

Subjects:

Comparison of periodicity of selected clock mutants. by Julian Bigge (22331861)

Subjects:

System overview showing stackable Hatching-Boxes. by Julian Bigge (22331861)

Subjects:

Archive containing manufacturing files. by Julian Bigge (22331861)

Subjects:

Screenshot a the Hatching-Box server application (HB-server). by Julian Bigge (22331861)

Subjects:

Performance analysis of the trained YOLOv7 models. by Julian Bigge (22331861)

Subjects:

Performance analysis for identity preserving tracking. by Julian Bigge (22331861)

Subjects:

Class confusion evaluation for the trained YOLOv7-tiny model. by Julian Bigge (22331861)

Subjects:

Overview of the proposed hardware architecture. by Julian Bigge (22331861)

Subjects:

Spatial distribution of wildtype <i>D. melanogaster</i> in larval and adult stage. by Julian Bigge (22331861)

Subjects:

Decomposition of Ctrl_MULT_MOD circuit into lower-level operations. by A. V. Antipov (13047338)

Sample lightning stroke data. by Manxing Shi (22367181)

“…Although density-based clustering algorithms can identify clusters of arbitrary shapes at fine scales, their performance is often hindered by large data volumes and significant variations in lightning density. …”

Similar to Fig 7, but for the year 2014. by Manxing Shi (22367181)

“…Although density-based clustering algorithms can identify clusters of arbitrary shapes at fine scales, their performance is often hindered by large data volumes and significant variations in lightning density. …”

Similar to Fig 7, but for the year 2015. by Manxing Shi (22367181)

“…Although density-based clustering algorithms can identify clusters of arbitrary shapes at fine scales, their performance is often hindered by large data volumes and significant variations in lightning density. …”

Single-cell based multiple instance learning predicts AML genetic subtypes with high accuracy and identifies clinically relevant cells. by Matthias Hehr (14797745)

“…(b) Our single-cell based explainable multiple instance learning algorithm (SCEMILA) classifies patients with an arbitrary number of single-cell images and sorts them by attention. …”

Multi-functional liquid crystal devices based on random binary matrix algorithm by Tibin Zeng (10890697)

“…However, based on the existing schemes there are still some challenges in fabricating the diffraction gratings with the controllable and arbitrary diffraction intensity of each order, multiple phase distribution, and polarisation of the output. …”