ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation حسب Hong Zhu (109912)

"…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. …"

ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation حسب Hong Zhu (109912)

"…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. …"

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

"…<div><p>The multi-armed bandit (MAB) problem is a classical problem that models sequential decision-making under uncertainty in reinforcement learning. …"

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" حسب Krishnendu Chatterjee (15367413)

"…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…"

<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b> حسب Richard McDowell (7311011)

"…</p><p dir="ltr">Models: R code to explore different models for implementation via Python in ArcGIS</p><p dir="ltr">!…"

Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection حسب Huichao Yin (14589020)

"…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…"

<b>Data Availability</b> حسب Bonyad Ahmadi (20750327)

"…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…"

<b>Data Availability</b> حسب Bonyad Ahmadi (20750327)

"…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…"

<b>Algorithm Pseudocode</b> حسب Yibin Zhao (22425801)

"…The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …"

Reproducible Code and Data for figures حسب Bonyad Ahmadi (20750327)

"…<br>✅ <b>Generated Figures</b> – High-resolution images illustrating model outputs and analytical results.<br>✅ <b>Machine Learning Models</b> – Implementation of <b>K-Nearest Neighbors (KNN) regression</b> with different distance metrics (<b>Mahalanobis, Fuzzy Mahalanobis, Euclidean</b>).…"

Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space حسب chenchen Guo (21327470)

"…/CAH-GKGE/model/supplementary instruction.md </p>…"

Supplementary Material حسب Aris Shahbazian (22464325)

"…The supplementary material includes the full Python-based implementation of the AI-driven optimization framework described in the manuscript. …"

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

"…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…"

High-throughput chemical genetics screen and titration of hit compounds vinblastine and vincristine. حسب Emiri Nakamura (21601773)

"…Scale bar = 100μm. (F) Fiji and Python scripts were used to process, analyze, and plot the high-content high-throughput confocal imaging data. …"

NanoDB: Research Activity Data Management System حسب Lorenci Gjurgjaj (19702207)

"…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …"

Digital Twin for Chemical Sciences حسب Jin Qian (19339035)

"…Lastly, we use the Figure 4.ipynb notebook in the 3_outputs folder to plot the subfigures in d), e), f). Observing that Basin Hopping performs better than Gaussian Process, we plot the degeneracy result with 0.1 error cutoff to obtain the subfigures in g), h), i). …"

Minami_etal_2025 حسب Keiichi Mochida (4670800)

"…<h2>Code files related to Minami et al (2025)</h2><p dir="ltr">accession_plot.py:Python script used to generate Fig4a.</p><p dir="ltr">Bd21-3_Bd21.Rmd:R script (mrkdown) used to run rQTL and generte Supplementary Fig. 3c (Bd21-3 x Bd21)</p><p dir="ltr">.…"

Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series حسب Andrew M. Thomas (712104)

"…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…"

A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture حسب Nagarajan Kandasamy (8400168)

"…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …"

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.…"