Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements حسب Pascal Wang (10130612)

"…In `main.py`, the parameters for the TAMS algorithm are specified (trajectory time, time step, score function, number of particles, type of score threshold, maximum number of iterations, noise level etc.). …"

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

Search Algorithms and Loss Functions for Bayesian Clustering حسب 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. …"

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

الموضوعات:

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

الموضوعات:

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

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

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

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

الموضوعات:

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

الموضوعات:

Changes in loss values for different algorithms. حسب Xiaojun Wang (50332)

الموضوعات:

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

الموضوعات:

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

الموضوعات:

Loss function variation curve. حسب Chunhua Yang (346871)

الموضوعات:

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب 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). …"

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

الموضوعات:

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

الموضوعات:

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"

The losses of the training process before and after the optimization of loss function. حسب Peihan Wen (6324315)

الموضوعات:

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

Loss Function Comparison. حسب Hongwei Yue (574068)