Researchers from the USC Viterbi School of Engineering are presenting 24 papers at the 2025 International Conference on Learning Representations (ICLR), Apr. 24-28, one of the premier global ...

Recent advances in robotics and machine learning have enabled the automation of many real-world tasks, including various ...

The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance ...

In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes ...

The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance ...

MIT researchers made a technique that improves the trustworthiness of machine-learning models, which could help improve the accuracy and reliability of AI predictions for high-stakes settings such ...

Neural networks power today’s AI boom. To understand them, all we need is a map, a cat and a few thousand dimensions.

Abstract: Object-based analysis is widely used for extracting information from satellite data using machine learning, offering reduced sensitivity to fine-scale variability, noise, and computational ...

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

A common view in current machine learning research is that machine learning itself can be used to improve the quality of AI ...

Researchers have developed a new artificial intelligence (AI) technique that brings machine vision closer to how the human brain processes images. Called Lp-Convolution, this method improves the ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...