PTPC-UHT bounce by David Parry (22169299)

“…<br>It contains the full Python implementation of the PTPC bounce model (<code>PTPC_UHT_bounce.py</code>) and representative outputs used to generate the figures in the paper. …”

Code and data for reproducing the results in the original paper of DML-Geo by Pengfei CHEN (8059976)

“…<p dir="ltr">This asset provides all the code and data for reproducing the results (figures and statistics) in the original paper of DML-Geo</p><h2>Main Files:</h2><p dir="ltr"><b>main.ipynb</b>: the main notebook to generate all the figures and data presented in the paper</p><p dir="ltr"><b>data_generator.py</b>: used for generating synthetic datasets to validate the performance of different models</p><p dir="ltr"><b>dml_models.py</b>: Contains implementations of different Double Machine Learning variants used in this study.…”

Data sets and coding scripts for research on sensory processing in ADHD and ASD by Vesko Varbanov (9687029)

“…The repository includes raw and matched datasets, analysis outputs, and the full Python code used for the matching pipeline.</p><h4>Ethics and Approval</h4><p dir="ltr">All procedures were approved by the University of Sheffield Department of Psychology Ethics Committee (Ref: 046476). …”

Datasets To EVAL. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

Statistical significance test results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

How RAG work. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

OpenBookQA experimental results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

AI2_ARC experimental results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

TQA experimental results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

E-EVAL experimental results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

TQA Accuracy Comparison Chart on different LLM. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

ScienceQA experimental results. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

Code interpreter with LLM. by Jin Lu (428513)

“…To address these issues, we propose a system that utilizes RAG to dynamically retrieve up-to-date, relevant information from external knowledge sources, thus mitigating the common “hallucination” problem in LLMs. …”

Code for High-quality Human Activity Intensity Maps in China from 2000-2020 by Wenqi Xie (18273238)

“…<p dir="ltr">Code and remote sensing images and interpretation results of the samples for uncertainty analysis for "High-quality Human Activity Intensity Maps in China from 2000-2020"</p><p dir="ltr">“Mapping_HAI.py”：We generated the HAI maps using ArcGIS 10.8, and the geoprocessing tasks were implemented using Python 2.7 with the ArcPy library (ArcGIS 10.8 + Python 2.7 environment). …”

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

“…Each lane includes 'geometry' and 'inter_id' attributes.</li></ul><h2>Codes</h2><p dir="ltr">This repository contains the following Python codes：</p><ul><li>`data_processing.py`: Contains the implementation of data processing and feature extraction. …”

MATH_code : False Data Injection Attack Detection in Smart Grids based on Reservoir Computing by Carl-Hendrik Peters (21530624)

“…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…”

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

“…</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.…”

Monte Carlo Simulation Code for Evaluating Cognitive Biases in Penalty Shootouts Using ABAB and ABBA Formats by Raul MATSUSHITA (10276562)

“…<p dir="ltr">This Python code implements a Monte Carlo simulation to evaluate the impact of cognitive biases on penalty shootouts under two formats: ABAB (alternating shots) and ABBA (similar to tennis tiebreak format). …”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”