Comprehensive genomic testing in routine cancer care pathways has created the need to interpret the consequences of somatic (acquired) genomic variants beyond the currently well-characterised driver ...
Abstract: Effective classification of Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions is essential for optimizing communication performance in UAV-assisted networks, where signal quality, ...
ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...
Abstract: The transmission line is the most important component of the power system. Classifying the faults occurring on the transmission line helps the system operator activate the mechanism of ...
Learn how to classify sleep stages using EEG data with Python, MNE, and Scikit-learn in this step-by-step guide. House GOP fails to pass tax and spending bill after key committee vote Game of Thrones: ...
Hands-on coding of a multiclass neural network from scratch, with softmax and one-hot encoding. #Softmax #MulticlassClassification #PythonAI Trump announces two new national holidays, including one on ...
This project is a simple spam message classifier built using Python's Scikit-learn library. It uses a Multinomial Naive Bayes model combined with a Count Vectorizer to classify text messages as either ...
Layer wise Scaled Gaussian Priors for Markov Chain Monte Carlo Sampled deep Bayesian neural networks
1 School of Computer Science, Technological University Dublin, Dublin, Ireland 2 ADAPT Research Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland Previous work ...
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