Presentation4_Serial Electron Diffraction Data Processing With diffractem and CrystFEL.PDF by Robert Bücker (10825188)

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Subjects:

ProSmith model overview. by Alexander Kroll (9304225)

Subjects:

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

Hyperparameters of the ProSmith gradient boosting models. by Alexander Kroll (9304225)

Subjects:

Data_Sheet_1_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.pdf by Stefano Casali (6703274)

Data_Sheet_2_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.ZIP by Stefano Casali (6703274)

Data_Sheet_2_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.ZIP by Stefano Casali (6703274)

Data_Sheet_1_Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.pdf by Stefano Casali (6703274)

Python and sql scripts to disaggregate annual emissions into high time resolution data by Greet J. Maenhout (8121812)

“…The file named 'Python_sql_codes_to_implement_temp_profiles.zip' contains the Python codes and some sql scripts used to apply temporal profiles to disaggregate EDGAR annual emissions into higher time resolution data. …”

Core concepts implemented in the MetDataModel package. by Joshua M. Mitchell (14703178)

Comparison of window size for embedding with Wordnet synonym replacement (WN) and without (PM). While Table 1 compared the effects of different values of using a window size of 10,... by Enock Niyonkuru (21246879)

Subjects:

Comparison of Monod model fit with linear error model. by Laura Marie Helleckes (12206910)

Subjects:

The logical blocks of the epithelial model implementation. by Leyla Noroozbabaee (14100772)

Subjects:

DataSheet1_OSAFT Library: An Open-Source Python Library for Acoustofluidics.zip by Jonas Fankhauser (12895304)

“…Our code is designed to be extensible. A library of fluid and solid material models facilitates the implementation of new theories. …”

Data_Sheet_1_Brian2CUDA: Flexible and Efficient Simulation of Spiking Neural Network Models on GPUs.pdf by Denis Alevi (11805765)

“…These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. …”

Diagnostic plots of model fits. by Laura Marie Helleckes (12206910)

Subjects:

SecurityGuidelinesRetrievalForPythonCodeGen by Catherine Tony (18368913)

“…Using Task-Specific Guidelines for Secure Python Code Generation: Replication Package"</p><p dir="ltr">This replication package contains SecGuide along with the results of each step followed in its creation, the scripts that implement all the prompting approaches and the code generated by the LLMs using these approaches. …”

Replacing the final prediction layer of end-to-end trained Transformer Networks with gradient boosting models improves performance. by Alexander Kroll (9304225)

Subjects:

Python implementation of the geometric minimum action method (gMAM) by Pascal Wang (10130612)

“…<p>The Python 3 script <code>gmam_demo.py</code> found in this repository implements the geometric minimum action method (gMAM) as presented in Heymann, M. and Vanden-Eijnden, E. (2008), "The geometric minimum action method: A least action principleon the space of curves." …”