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. …”

Loss function variation curve. by Chunhua Yang (346871)

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

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

Comparison of details of different algorithms. by Hao Wu (65943)

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Structure of the LMPEC algorithm model. by Hao Wu (65943)

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Sub-network model structure in the LMPEC algorithm. by Hao Wu (65943)

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Probably pathogenic variants (algorithms). by Felipe Fidalgo (642532)

Slicing aided hyper inference algorithm. by Chunhua Yang (346871)

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Loss Function Comparison. by Hongwei Yue (574068)

Loss Function Comparison. by Hongwei Yue (574068)

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

Convergence curve of unimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

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Convergence curve of unimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

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Antihypertensive treatment algorithm. by Kira Bang Bove (9607123)

Limitation of the conventional DBT reconstruction algorithm. by Yunsu Choi (11993484)

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

“…For a RDKit molecule, it provides (i) a PNG binary string with an image of the molecule with color-highlighted functional groups; (ii) a list of sets of atom indices (idx), each set corresponding to a functional group; (iii) a list of pseudo-SMILES canonicalized strings for the full functional groups; and (iv) a list of RDKit labeled mol objects, one for each full functional group. …”

Performance comparison of YOLOv8n adding different loss functions. by Wenyuan Xu (2553028)

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Graph of YOLOv8n detection results with different loss functions. by Wenyuan Xu (2553028)

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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). …”