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An expectation-maximization algorithm for finding noninvadable stationary states.
Published 2020“…<i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”
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EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit
Published 2025“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”
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Comparison of deconvolution and optimization algorithms on a batch of data.
Published 2021“…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). …”
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Machine learning algorithm parameters.
Published 2023“…Results of the study showcased that both systems can simulate river flows as a function of catchment rainfalls; however, the Cat gradient Boosting algorithm (CatBoost) has a computational edge over the Adaptive Network Based Fuzzy Inference System (ANFIS). …”
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Procedure of the DCT-based EIT algorithm.
Published 2023“…To demonstrate the increased interpretability of the EIT image through structural prior in the DCT-based approach, the DCT-based reconstructions were compared with reconstructions from a widely applied one-step Gauss-Newton solver with background prior and from the advanced GREIT algorithm. The comparisons were conducted both on simulation data and retrospective patient data. …”
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…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). …”
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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
Published 2025“…</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.…”
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Results of the application of different clustering algorithms to average functional connectivity from healthy subjects.
Published 2023“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”
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A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data
Published 2022Subjects: -
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Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements
Published 2021“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”
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PyNoetic’s stimuli generation and recording module, which supports both ERP and SSVEP.
Published 2025Subjects: -
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