<b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b> حسب Pajtim Zariqi (22155799)

<b>Altered cognitive processes shape tactile perception in autism.</b> (data) حسب Ourania Semelidou (19178362)

"…The perceptual decision-making setup was controlled by Bpod (Sanworks) through scripts in Python (PyBpod, https://pybpod.readthedocs.io/en/latest/). …"

DeepB3Pred - code حسب Saleh Musleh (22263718)

MCCN Case Study 3 - Select optimal survey locality حسب Donald Hobern (21435904)

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

<b>DeepB3Pred</b> حسب Saleh Musleh (22263718)

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

"…</p><h3><b>Model training</b></h3><h4><code>python train_GTN.py</code></h4><p dir="ltr">This step trains the GTN model. …"

Recursive generation of substructures using point data حسب Jackie R (18359715)

Global Graph Dataset حسب Winston Yap (13771969)

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

"…The database also includes three averaged multi-model ensembles produced for each of the four emission scenarios:</p><p>**************************************************************************************************************************</p><p dir="ltr">The Global Aridity Index (Global-AI) and Global Reference Evapo-Transpiration (Global-ET0) datasets provided in Version 3.1 of the Global Aridity Index and Potential Evapo-Transpiration (ET0) Database (Global-AI_PET_v3.x1) provide high-resolution (30 arc-seconds) global raster data for the 1970-2000 period, related to evapotranspiration processes and rainfall deficit for potential vegetative growth, based upon implementation of the FAO-56 Penman-Monteith Reference Evapotranspiration (ET₀) equation.…"

Data files accompanying our PLoS One publication حسب Peter Hinow (21810605)

"…The videos were digitized and the positional data were saved in .xlsx or .csv format, respectively. The python codes contain the numerical implementations of our mathematical models.…"

DeepB3Pred_source_code حسب Muhammad Arif (17012472)

Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> حسب Zhou (20184816)

"…</p><p dir="ltr">GPU：NVIDIA GeForce RTX 3090 GPU</p><p dir="ltr">Bert-base-cased pre-trained model: https://huggingface.co/google-bert/bert-base-cased</p><p dir="ltr">python=3.7，pytorch=1.9.0，cudatoolkit=11.3.1，cudnn=8.9.7.29.…"

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

"…</p><p dir="ltr"><b>ridge_gwr.py</b>: Implementations of a modified Geographically Weighted Regression (GWR) with ridge regression</p><p dir="ltr"><b>ridge_sel_bw.py</b>: Implementations of a modified selector of band width in GWR with ridge regression</p><p dir="ltr"><b>scenario_manager.py</b>: Functions to create simulation scenarios</p><p dir="ltr"><b>utility.py</b>: Functions for testing spatial causal effects using different models and placebo tests for inference.…"

Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data حسب Jeanette Leue (22470409)

"…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …"

Probabilistic-QSR-GeoQA حسب Mohammad Kazemi (19442467)

"…Also we have written Python API for Probcog (ProbCog-API.py) and SparQ reasoners (SparQ-API.py).…"

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. …"

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

"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"

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

"…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"

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. …"