Data and Code for 'A Comparative Study of Physics-Informed and Data-Driven Neural Networks for Compound Flood Simulation at River-Ocean Interfaces: A Case Study of Hurricane Irene' by Dongyu Feng (21196556)

“…<br><br>conda create --name tf2 --file requirement_tf2.txt<br>conda activate tf2<br><br><br>### Before training<br>Before running the code, need to create folders to save the model output<br><br>For CNN, create /files/CNN<br><br>For PINNs, create /saved_model<br><br>For saving figures from visualization, create /figures<br><br></p><p dir="ltr">Training and Results</p><p dir="ltr"><br>PINNs<br>Training: To train the model, run:</p><p dir="ltr">python PINN_test_bnd_uh_Telemac.py</p><p dir="ltr">python PINN_test_bnd_uh_Telemac_FDM.py<br></p><p dir="ltr">Result Plotting and Comparison: For plotting and comparing results, use:</p><p dir="ltr">python PINN_plot_comparison.py<br><br><br>Data-driven Model<br>CNN Training: To train the CNN model, execute:</p><p dir="ltr">python train_CNN.py<br><br>Result Visualization: To visualize the results of the CNN model, run:</p><p dir="ltr">python predict_CNN.py<br><br>To reproduce all results and figures in the manuscript, please refer to the scripts in analysis/</p>…”

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

“…The repository contains all necessary data and code for reproducing the analyses of beetle breeding phenology predictions using circadian activity patterns.…”

DRLiPS: A Novel Method for Prediction of Druggable RNA-Small Molecule Binding Pockets Using Machine Learning by Sowmya Ramaswamy Krishnan (20867198)

Western Oregon Wet Dry (WOWTDR) annual predictions of late summer streamflow status for western Oregon, 2019-2021 by Jonathan D. Burnett (19659601)

“…Also included is all R code and Python code needed to run and process this model.…”

Submit to AGU-Manuscript-Enhancing Landslide Displacement Prediction Using a Spatio-Temporal Deep Learning Model with Interpretable Features by Jia Wang (20526992)

“…It includes the monitoring data and model prediction results in two Excel files, along with the corresponding Python code used in the study. …”

Liang et al., 2024_CEE_BrGMM_BAE: A Clustering Model for Predicting Freshwater and Halo-Alkaliphilic Bacterial Assemblages Using brGDGTs by Jie Liang (14213144)

“…</p><p dir="ltr"><b>Features</b>:</p><ul><li><b>User-Friendly GUI</b>: For users unfamiliar with Python, we've developed a graphical user interface (GUI) that enables predictions without the need to install or run Python code.…”

ML model for prediction of postpartum rehospitalization in pregnant women/new mothers using readily obtainable pre-pregnancy or early pregnancy sociodemographic and health determin... by Martin Frasch (5754731)

“…</li><li>We also share the R/SAS/Python codes for causal inference analyses on this and similar datasets.…”

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification by Mohammed Nasser Al-Andoli (21431681)

MLP_mod_application_v2.zip by Jian Li (20881226)

“…<p dir="ltr">The python source code for predicting the spatial location of macrophages using single cell dataset. …”

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" by 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.…”

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

“…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

Discovery of a Latent Entropy-Based Physiologic State Variable Governing Multisystem Instability in Critical Illness by Jordan Rabbani (22800074)

Tipping points of marine phytoplankton to multiple environmental stressors by Zhan Ban (11627098)

Data for: An effective methodology to quantify cooling demand in the UK housing stock by Lloyd Corcoran (19094369)

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

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by 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. …”

The data of the paper "Remote spectral detection of canopy functional strategies varying within and across forest types". by Fengqi Wu (20149158)

“…Canopy_2024_PLSR_ST_canopy_run_refit.py</p><p dir="ltr">This is the python code used for PLSR modeling.</p><p dir="ltr"><br></p><p dir="ltr">3. python_code_get_model_details.zip</p><p dir="ltr">This is the python code to get model performance, coefficients, VIPs, and so on.…”

Monte Carlo Simulation for SAPAL Framework: AI-Augmented CI/CD Reliability by Rohit Dhawan (22457026)

“…</p><p dir="ltr">Files included: <br>- simulation.py: Python simulation code <br>- README.md: Complete documentation and methodology <br><br>This code supports the paper "AI-Augmented Reliability in Continuous Integration and Deployment: A Conceptual Framework for Predictive, Adaptive, and Self-Correcting Pipelines".…”

The Transcriptional Gradient in Negative-Strand RNA Viruses Suggest a Common RNA Transcription Mechanism: Model by Jean Peccoud (275555)

“…</p><p dir="ltr">Notebook2 contains the python code for making predictions of transcriptional gradients for gene-shuffled variants.…”