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model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
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model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
python based » method based (Expand Search), person based (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
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81
Comparison of BlueRecording with existing tools
Published 2025“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”
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82
The format of the weights file
Published 2025“…To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an <i>in silico</i> model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.…”
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83
Flowchart representation of lion optimization algorithm for hyperparameter tuning in the HCAP model.
Published 2025Subjects: -
84
MYTHOS: A Python Interface for Surface Crystal Structure Prediction of Organic Semiconductors
Published 2025“…We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. …”
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85
Five Operator Lattice Simulation
Published 2025“…<p dir="ltr">This dataset contains the Python simulation code and supporting documentation for the paper <i>A Five-Operator Lattice of Consciousness: A Logical Framework for Mediation Between Implicit and Explicit Processing</i> (McDaniel, 2025).…”
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Overview of deep learning terminology.
Published 2024“…<div><p>Convolutional neural network (CNN)-based deep learning (DL) methods have transformed the analysis of geospatial, Earth observation, and geophysical data due to their ability to model spatial context information at multiple scales. …”
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89
Scripts, data and figures underpinning 'Towards the Creation of Legible Octilinear Power Grid Diagrams Using Mixed Integer Linear Programming'
Published 2024“…<p dir="ltr">These Python notebooks implement the techniques described in the paper "Towards the Creation of Legible Octilinear Power Grid Diagrams Using Mixed Integer Linear Programming".…”
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Local Python Code Protector Script: A Tool for Source Code Protection and Secure Code Sharing
Published 2024“…</p><h2>Key Features</h2><ul><li><a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Code Obfuscation in Python</b></a>: Implements multi-level protection with dynamic encryption and obfuscation techniques, making it an effective <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Python obfuscator</b></a>.…”
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91
BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories
Published 2025“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories
Published 2025“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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93
BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories
Published 2025“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool
Published 2024“…This tool provides <a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank">code obfuscation in Python</a> and <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank">Python code encryption</a>, enabling developers to <a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank">protect Python code</a> effectively.…”
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Online Resource 3: Word Cloud Dataset and Code
Published 2025“…This set of files are part of Online Resource 3, which allows readers to implement a Jupyter Notebook Python program to create a word cloud based on survey responses. …”
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Efficient, Hierarchical, and Object-Oriented Electronic Structure Interfaces for Direct Nonadiabatic Dynamics Simulations
Published 2025“…We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. …”
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Numerical data and codes for "Noisy Probabilistic Error Cancellation and Generalized Physical Implementability"
Published 2025“…<p dir="ltr">This data set contains the data and codes for "Noisy Probabilistic Error Cancellation and Generalized Physical Implementability". We numerically simulate the bias of noisy probabilistic error cancellation with noisy Pauli operations and the bias of error model violation.…”
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