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

“…<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. …”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

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Signal detection algorithm adapted from [1] yields exponential distributions and unrealistic mean durations of percepts. by Quynh-Anh Nguyen (847240)

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

Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

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Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

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Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Comparison of output voltage with adaptive algorithm. by Kai Zhou (125548)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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

Performance profiles of these algorithms on the basis of the number of function evaluations. by Xianfeng Ding (535904)

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). …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by 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.…”