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. …”

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

State Function-Based Correction: A Simple and Efficient Free-Energy Correction Algorithm for Large-Scale Relative Binding Free-Energy Calculations by Runduo Liu (10756379)

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Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

Auto-tuning algorithm of the weight factors in the cost function. by Syed Umaid Ali (14486372)

“…<p>Auto-tuning algorithm of the weight factors in the cost function.…”

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

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

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The probability density function for cost function g(X). by Matheus Sant’Ana Lima (9937809)

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

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

The obtained cost function values with respect to each run of different algorithms. by Davut Izci (15927452)

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Table_2_Visuospatial, oculomotor, and executive reading skills evolve in elementary school, and errors are significant: a topological RAN study.pdf by Mario Lecce (18777553)

Table_1_Visuospatial, oculomotor, and executive reading skills evolve in elementary school, and errors are significant: a topological RAN study.pdf by Mario Lecce (18777553)

Flowchart of proposed fitness function algorithm. by Ferhat Yuna (21519851)

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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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Performance comparison of recent and effective algorithms for minimizing error-based cost functions. by Davut Izci (15927452)

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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). …”

Cost function with VPLE. by Ijaz Ahmed (1545961)

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Cost function depending on the waiting time. by Ludovica Adacher (11238189)

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)