Abstract: Shuffled linear regression (SLR) seeks to estimate latent features through a linear transformation, complicated by unknown permutations in the measurement dimensions. This problem extends ...

This study presents a potentially valuable exploration of the role of thalamic nuclei in language processing. The results will be of interest to researchers interested in the neurobiology of language.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Mouse primary motor and somatosensory cortices contain detailed information about the many time-varying arm and paw joint angles during reaching and grasping, implying a 'low-level' role in ...

Abstract: The aim of this paper is to present the results of literature survey on the application of simple and multiple linear regression (to be called regression henceforth in this paper) technique ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

From the first 5 rows of the dataset, we can see that there are several columns available: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, and sex. There also appears ...

A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how systems evolve over time and reduces thousands of variables into compact ...

Duke researchers have built an AI that uncovers simple laws behind complex, ever-changing systems by learning directly from data. The result is clear, compact models that help scientists understand, ...