Loss function value changes in CNN training changes with epochs for both training dataset and testing dataset. by Jiaxi Wang (545353)

Loss Function Comparison. by Hongwei Yue (574068)

Loss Function Comparison. by Hongwei Yue (574068)

Acc epoch loss curve of IPCA algorithm. by Lu Lin (201289)

Filled contour plot based on histograms of the occurence-frequency of binned values of and as a function of . by Paul Kinsler (3975620)

Siou loss function calculation diagram. by Weiyu Han (3448742)

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Filled contour plot based on histograms of the occurence-frequency of binned values of and as a function of rate ratio . by Paul Kinsler (3975620)

AUC scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

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Recall scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

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F1-scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

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Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

Network structure diagram of LMD-YOLO algorithm. by Weiyu Han (3448742)

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Network structure diagram of YOLOv8 algorithm. by Weiyu Han (3448742)

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If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

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Illustration of the perturbation of the protein relationship network and NECARE algorithm. by Jiajun Qiu (4684921)

Comparison of packet loss quantity. by Jianpeng Zhang (528185)

“…The research results demonstrated the great performance of the suggested algorithm in each test function as well as the positive effects of the optimization search. …”

Comparison with the BST algorithm for the AF and CST bundles. by Thomas Durantel (20933812)

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Comparison of deconvolution and optimization algorithms on a batch of data. by Ali-Kemal Aydin (10968731)

“…Output is given by the vascular response, measured as the change in speed of red blood cells flowing inside a capillary proximal to the recorded neuronal activation (in yellow, right panel). Both experimental data have been resampled at 50ms and used to compute a set of TFs (in orange) either with direct deconvolution approaches (Fourier or Toeplitz methods, middle-upper panel TFs) or with 1-Γ function optimization performed by 3 different algorithms (middle-lower panel TFs). …”

Search Algorithms and Loss Functions for Bayesian Clustering by David B. Dahl (11761055)

“…<p>We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. …”

Evolution of the rescaled hydraulic diameter () and complexity () in both simulations and seal tomograms as a function of simulation timestep and relative age (). by Jonathan E Kings (20818367)