SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

Comparison of performance between our next reaction implementation and the Python library from Ref. [3]. by Samuel Cure (22250922)

Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... by Ziyan Jin (21021976)

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…We used the common interface provided by Neuroptimus to conduct a detailed comparison of more than twenty different algorithms (and implementations) on six distinct benchmarks that represent typical scenarios in neuronal parameter search. …”

Python code for hierarchical cluster analysis of detected R-strategies from rule-based NLP on 500 circular economy definitions by Zahir Barahmand (18008947)

“…</p><p dir="ltr">This Python code was optimized and debugged using ChatGPT-4o to ensure implementation efficiency, accuracy, and clarity.…”

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. …”

Segmentation module training details. by Khelina Fedorchuk (19130089)

Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

“…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by 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. …”

Overview of deep learning terminology. by Aaron E. Maxwell (8840882)

“…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …”

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.…”

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

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

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

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by 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.…”

Overview of generalized weighted averages. by 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. …”

Summary of Tourism Dataset. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Segment-wise Spending Analysis. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”