Showing 281 - 300 results of 317 for search '(( python model implementation ) OR ( python code representing ))', query time: 0.41s Refine Results
  1. 281

    Social media images of China's terraces by Song Chen (19488280)

    Published 2025
    “…Geo-tagged images were collected using Weibo cookies and Python-based scraping tools (available at: https://github.com/dataabc/weibo-search). …”
  2. 282

    Automatic data reduction for the typical astronomer by Bradford Holden (21789524)

    Published 2025
    “…PypeIt has been developed by a small team of astronomers with two leading philosophies: (1) build instrument-agnostic code to serve nearly any spectrograph; (2) implement algorithms that achieve Poisson-level sky-subtraction with minimal systematics to yield precisely calibrated spectra with a meaningful noise model. …”
  3. 283

    World Heritage documents reveal persistent gaps between climate awareness and local action by Yang Chen (20756166)

    Published 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. …”
  4. 284

    Reinforcement Learning based traffic steering inOpen Radio Access Network (ORAN)- oran-ts GitHub Repository by Aaradhy Sharma (21503465)

    Published 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. …”
  5. 285

    Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution by Giorgio Boccarella (22810952)

    Published 2025
    “…This file can be used together with the analysis code (link to be added upon publication) to generate all figures.…”
  6. 286

    Evaluation and Statistical Analysis Code for "Multi-Task Learning for Joint Fisheye Compression and Perception for Autonomous Driving" by Basem Ahmed (18127861)

    Published 2025
    “…</li></ul><p dir="ltr">These scripts are implemented in Python using the PyTorch framework and are provided to ensure the reproducibility of the experimental results presented in the manuscript.…”
  7. 287

    Supervised Classification of Burned Areas Using Spectral Reflectance and Machine Learning by Baptista Boanha (22424668)

    Published 2025
    “…<p dir="ltr">This dataset and code package presents a modular framework for supervised classification of burned and unburned land surfaces using satellite-derived spectral reflectance. Six Python scripts are provided, each implementing a distinct machine learning algorithm—Random Forest, k-Nearest Neighbors (k-NN), Multi-Layer Perceptron (MLP), Decision Tree, Naïve Bayes, and Logistic Regression. …”
  8. 288

    Copy number contingency table. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  9. 289

    Gene mutation contingency table. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  10. 290

    Resistant & sensitive cell line Info on AZD5991. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  11. 291

    Resistant & sensitive drug info on COLO800. by Yang Wu (66682)

    Published 2025
    “…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…”
  12. 292

    Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> by Hao Chen (20313552)

    Published 2025
    “…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…”
  13. 293

    Data Sheet 1_Nationwide epidemiological study of subarachnoid hemorrhage: trends in admissions, mortality, seasonality, costs, clipping, embolization, and the impact of COVID-19.pd... by Thiago Oscar Goulart (22485604)

    Published 2025
    “…</p>Methods<p>This retrospective study analyzed secondary data from the Brazilian public health system (DataSUS) using ICD-10 code I60 for aSAH. Key metrics included the evaluation of admissions with time-series in Python, and mortality rates, procedures, and costs.…”
  14. 294

    2024 HUD Point in Time Count Data by State and CoC with Serious Mental Illness and Chronic Substance Use Counts by Benjamin Gorman (21648794)

    Published 2025
    “…</p><p dir="ltr">HUD PIT Count reports for states, Washington, DC, and the 384 CoCs were systematically downloaded from the HUD Exchange website using a Python script developed using Cursor software. Cursor uses large language models, especially Claude Sonnet 4 (Anthropic), to generate code. …”
  15. 295

    Electrical Tactile Dataset (Piezoelectric and Accelerometer) for textures by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, sensor index)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  16. 296

    OHID-FF dataset for forest fire detection and classification by xin chen (20496938)

    Published 2025
    “…</p><p dir="ltr">- Pointed to the `train val scripts/` README for model-specific commands and dependencies.</p>…”
  17. 297

    Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

    Published 2025
    “…<br><br><b>Missing-Data Handling & Imputation:</b></p><p dir="ltr">The following sequential steps were applied to create a complete and consistent daily time series suitable for analysis (presented in the Imputed_AP_Data_Zurich_2010-25 sheet), particularly addressing the absence of routine PM₂.₅ measurements prior to January 2016. The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”
  18. 298

    Phylogenomics of aquatic bacteria by Krzysztof Jurdzinski (12519700)

    Published 2025
    “…</p> <p><br></p> <p>all_MSG_ids.txt - a text file with names of all the representative MAGs within all the MSG pairs.</p> <p><br></p> <p>filter_MSGs.py - a Python script to extract the MAGs from within the MSGs (given all_MSG_ids.txt) from a folder containing a larger set of sequences.…”
  19. 299

    Optical Tactile (TacTip) Dataset for texture classification by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, h, w)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr"><br></p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  20. 300

    Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

    Published 2025
    “…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…”