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. …”

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Comparison results of the loss functions. by Jia Li (160557)

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APSO–CNN and FNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

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APSO–CNN and FNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

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Loss function values of target detection algorithms during training. by Guodong Su (7876934)

“…<p>Loss function values of target detection algorithms during training.…”

BEs with different loss functions. by Qin Gong (118801)

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Equivalence of loss functions and effects of regularization. by Jonathan Vacher (17041542)

Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Loss function variation curve. by Chunhua Yang (346871)

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APSO–WOA–CNN and FNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

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APSO–WOA–CNN and FNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

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

Performance comparison of different loss functions. by Junjie Lu (160350)

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Recursive attention function and loss function change. by Wang Linfeng (17102068)

Comparison of the curves of the DCIOU loss function and the CIOU loss function. by Xunqian Xu (21261899)

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Loss Function Comparison. by Hongwei Yue (574068)

Loss Function Comparison. by Hongwei Yue (574068)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

Comparative experimental data of loss functions. by Huiying Zhang (200681)

“…Additionally, three innovative loss functions—focalerDIoU, focalerGIOU and focalerShapeIoU are proposed to reduce losses during the training process. …”