Concurrent spin squeezing and field tracking with machine learning حسب Junlei Duan (18393642)

"…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …"

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas حسب Pedro Cabral (18947566)

"…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…"

Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) حسب Winston Yap (13771969)

"…</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. …"

Oka et al., Supplementary Data for "Development of a battery emulator using deep learning model to predict the charge–discharge voltage profile of lithium-ion batteries" حسب Kanato Oka (20132185)

"…For a single file, test data is read, and the prediction plot is output. To use this Python script, you need to modify the "CFG (config)" and "Convenient" sections within the script.…"

kececilayout حسب Mehmet Keçeci (14301782)

"…<p dir="ltr"><b>Kececi Layout (Keçeci Yerleşimi)</b>: A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.</p><p dir="ltr"><i>Python implementation of the Keçeci layout algorithm for graph visualization.…"

Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files) حسب Wubin Ding (11823941)

"…</p><p dir="ltr">PMID: 37824674</p><p><br></p><h2>How to download</h2><p dir="ltr">To quickly download the whole folder, Python package <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">pyfigshare</a> can be implemented. please refer to pyfigshare documentation: <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">https://github.com/DingWB/pyfigshare</a></p><p dir="ltr">for example: <code>figshare download 28424780 -o downlnoaded_data</code></p>…"

IGD-cyberbullying-detection-AI حسب Bryan James (19921044)

"…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…"

Overview of generalized weighted averages. حسب Nobuhito Manome (8882084)

"…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…"

Spotted owl habitat quality maps and disturbance attribution analysis حسب Josh Barry (7573823)

"…<p dir="ltr">This dataset includes annual spatial maps of spotted owl nesting habitat quality in Southern California and an accompanying ArcPython script used to attribute negative annual habitat change to wildfire (Barry et al., 2025). …"

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

"…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. …"

Concurrent spin squeezing and field tracking with machine learning حسب Junlei Duan (18393642)

"…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …"

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 حسب Robert Zomer (12796235)

"…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …"

Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems حسب Lakshit Mathur (20894549)

"…</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. Data are released under a Creative Commons Attribution-NonCommercial-4.0 (CC BY-NC 4.0) license; code under MIT License.…"

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) حسب Amanda Bueno de Moraes (22559249)

"…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …"

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

"…</p><p dir="ltr">complete_data.xlsx</p><p dir="ltr">A single Excel file containing 18 sheets with data from all figures:</p><p dir="ltr">Sheet names and descriptions:</p><ul><li>Fig_1: Probability of emergence contour data</li><li>Fig_2_b: MIC evolution simulation data</li><li>Fig_2_c: Speed of resistance evolution data</li><li>Fig_2_d: Time to resistance data</li><li>Fig_2_a_d_time_series_sim7: Simulation time series data (representative simulation, low persistence)</li><li>Fig_2_a_d_MIC_values_sim7: MIC values from simulation (representative simulation, low persistence)</li><li>Fig_2_a_p_time_series_sim5: Simulation time series data (representative simulation, high persistence)</li><li>Fig_2_a_p_MIC_values_sim5: MIC values from simulation (representative simulation, high persistence)</li><li>Fig_3_a-b: Distribution plot simulation data</li><li>Fig_3_a-b_empirical: Distribution plot empirical data</li><li>Fig_4_a: Mutation count simulation data</li><li>Fig_4_b: Mutation count empirical data</li><li>Fig_4_c: Mutation functional data</li><li>Fig_5_a-b: Large-scale simulation results (heatmap data)</li><li>Fig_5_c_mic: MIC heatmap empirical data</li><li>Fig_5_c_extinction: Extinction heatmap empirical data</li><li>Fig_6: Population size analysis simulation data</li><li>S1_figure: Supplementary experimental survival data</li></ul><p dir="ltr">Column naming convention</p><p dir="ltr">All sheets use consistent, tidy column names.…"

Missing Value Imputation in Relational Data Using Variational Inference حسب Simon Fontaine (7046618)

"…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …"

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

"…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"

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

"…</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>…"

Probabilistic-QSR-GeoQA حسب Mohammad Kazemi (19442467)

"…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …"

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 حسب Jordan Waters (21620558)

"…<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. …"