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

Schematic example of multiscale modelling implementation. حسب Robyn M. Stuart (3754000)

Tools used in implementing the RNN models. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

GraSPy: an Open Source Python Package for Statistical Connectomics حسب Benjamin Pedigo (6580352)

"…We developed GraSPy, an open-source Python toolkit for statistical inference on graphs. …"

Overview of the implemented simulation tool and training framework in Diffrax. حسب Paul van Lent (16876977)

Python script of the PREDICATE tool written in a Jupyter Notebook format. حسب Nantia Leonidou (14833068)

Analysis of the selected studies in terms of tools used for implementing RNN models. حسب Fahmi H. Quradaa (17896527)

الموضوعات:

Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management حسب Pavel Izosimov (20096259)

"…</li><li><b>Commercial Distribution</b>: Safely share Python code with clients or customers, implementing advanced <b>Python code protection tools</b> for sales or rentals.…"

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

الموضوعات:

Implementations benchmark. حسب Serena Aneli (17002149)

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

الموضوعات:

Re-Implementation of Refactory Tool حسب Aqsa Shabbir (18604261)

"…The file `requirements.txt` lists the python packages, along with their specific version number, required by the tool.…"

Python Implementation of HSGAdviser Chatbot: AI model for Sustainable Education حسب Suha Assayed (22454038)

"…<p dir="ltr">This repository contains the Python source code and model implementation for HSGAdviser, an AI speech assistant designed to provide personalized college and career guidance for high school students through conversational AI. …"

Listed python codes of our algorithm with explanations (Python 3.9 recommended). حسب Takayuki Niizato (162226)

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:

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:

Loss history of segmentation model trained over 600 epochs. حسب Owen M. O’Connor (11965460)

الموضوعات:

Low- and high-level subspace noise for the reverse-correlation of visual and audio stimuli. حسب Juan José Burred (6555578)

الموضوعات: