Compartmental BNGL implementation of the SNARE complex model. حسب Adam Husar (18437351)

الموضوعات:

Python code to instantiate the class Fractal. حسب Leonardo Costa Ribeiro (10439243)

Example of loading and running BNGL model in MCell4. حسب Adam Husar (18437351)

الموضوعات:

Recommended structure of a standard MCell4 model. حسب Adam Husar (18437351)

الموضوعات:

Total epithelial chloride fluxes for the W-PCT-E model. حسب Leyla Noroozbabaee (14100772)

SciPy2024: Facilitating scientific investigations from long-tail data with Python حسب Deborah Khider (4673140)

"…</p><p><br></p><p dir="ltr">Although the Pandas extension and its incorporation into Pyleoclim represents a major stepping stone to allow scientists in these domains to make use of more open science code, work remains for interoperability with other open source libraries such as Matplotlib, Seaborn, Scikit-learn, and Scipy. …"

Parallel pipeline elements. حسب Ramona Leenings (11167294)

Parallel plot showing hyperparameter exploration. حسب Ramona Leenings (11167294)

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,... حسب Enock Niyonkuru (21246879)

الموضوعات:

Representative schematic of the geometric configuration used for a 120 electrode MEA. حسب Christopher S. Dunham (12239618)

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

"…</p><p dir="ltr"><br></p><p dir="ltr">## Files in the Project</p><p dir="ltr"><br></p><p dir="ltr">### Python Scripts</p><p dir="ltr">- **Wildfire_on_m_n-CAk.py**: This file contains the main code for the fire cellular automaton. …"

Accuracy of the segmentation model. حسب Owen M. O’Connor (11965460)

الموضوعات:

Table_1_An application programming interface implementing Bayesian approaches for evaluating effect of time-varying treatment with R and Python.pdf حسب Chen Chen (6544)

"…Here, we introduce an application programming interface (API) that implements both BART and GP for estimating averaged treatment effect (ATE) and conditional averaged treatment (CATE) for the two-stage time-varying treatment strategies.…"

Reducing the size of the model to increase speed. حسب Owen M. O’Connor (11965460)

الموضوعات:

Training the model on segmentation with custom weight maps. حسب Owen M. O’Connor (11965460)

الموضوعات:

Impact of frame shifts on tracking model performance. حسب Owen M. O’Connor (11965460)

الموضوعات:

Code interpreter with LLM. حسب Jin Lu (428513)

"…We evaluated our proposed system on five educational datasets—AI2_ARC, OpenBookQA, E-EVAL, TQA, and ScienceQA—which represent diverse question types and domains. Compared to vanilla Large Language Models (LLMs), our approach combining Retrieval-Augmented Generation (RAG) with Code Interpreters achieved an average accuracy improvement of 10−15 percentage points. …"

Python sript. حسب Kan Jia (6438599)

Schematic of the pixelwise binary cross-entropy loss function used to train the segmentation and tracking models. حسب Owen M. O’Connor (11965460)

الموضوعات:

Utilizing variable background weight maps for training the model on debris. حسب Owen M. O’Connor (11965460)

الموضوعات: