Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...
This finalizes our definition of adversarial location: the pitcher’s ability to locate pitches where a particular batter gets ...
Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...
By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...
Netflix has partnered with Lionsgate to produce a brand-new sci-fi action movie starring Alan Ritchson, who is becoming a highly sought-after action star. Filming concluded in late 2024 and is ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
ABSTRACT: The stock market faces persistent challenges, including inefficiencies, volatility, and barriers to entry, which hinder its accessibility and reliability for investors. This paper explores ...
Abstract: We examine the problem of classifying biological sequences, and in particular the challenge of generalizing results to novel input data. We observe that the high-dimensionality of sequence ...
Weight decay and ℓ2 regularization are crucial in machine learning, especially in limiting network capacity and reducing irrelevant weight components. These techniques align with Occam’s razor ...
Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback