بدائل البحث:
model implementing » model implemented (توسيع البحث), model implementation (توسيع البحث), model representing (توسيع البحث)
tool implementing » trial implementing (توسيع البحث), from implementing (توسيع البحث), _ implementing (توسيع البحث)
python model » python code (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
model implementing » model implemented (توسيع البحث), model implementation (توسيع البحث), model representing (توسيع البحث)
tool implementing » trial implementing (توسيع البحث), from implementing (توسيع البحث), _ implementing (توسيع البحث)
python model » python code (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
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181
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182
Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan)
منشور في 2025"…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …"
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183
The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
منشور في 2025"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"
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184
The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
منشور في 2025"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"
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185
Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data
منشور في 2025"…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …"
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186
Error reduction over time by the HOFA-SMC.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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187
Comparison of SMC techniques.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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188
Proposed HOFA-SMC with experimental validation.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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189
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
منشور في 2025"…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …"
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190
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
منشور في 2025"…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …"
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191
Overview of generalized weighted averages.
منشور في 2025"…<div><p>The multi-armed bandit (MAB) problem is a classical problem that models sequential decision-making under uncertainty in reinforcement learning. …"
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192
Folder with all data and algorithms
منشور في 2025"…In this study, we present an open-source, Python-based computational framework that unifies photon transport modeling, probe geometry optimization, and photothermal safety assessment into a single workflow. …"
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193
World Heritage documents reveal persistent gaps between climate awareness and local action
منشور في 2025"…The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …"
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194
Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
منشور في 2025"…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…"
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195
Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
منشور في 2025"…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…"
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196
Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
منشور في 2025"…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…"
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197
Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
منشور في 2025"…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…"
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198
Reinforcement Learning based traffic steering inOpen Radio Access Network (ORAN)- oran-ts GitHub Repository
منشور في 2025"…It features a modular Python framework implementing various RL agents (Q-Learning, SARSA, N-Step SARSA, DQN) and a traditional baseline evaluated in a realistic cellular network environment. …"
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199
PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation
منشور في 2025"…PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation This release provides the complete, reproducible numerical implementation of the Parry Tensional Phase Collapse (PTPC) model — the dynamic core of the Universal Heartbeat Theory (UHT/PTPC). …"
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200
Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789
منشور في 2025"…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …"