A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and ...

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 ...

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected ...

On April 18, 2025, the United States Court of Appeals for the Federal Circuit ("Federal Circuit") issued a significant decision in ...

Our example projects demonstrate different use case scenarios of FEDn and its integration with popular machine learning frameworks like PyTorch and TensorFlow. Several hosting options are available to ...

Improvements in machine learning and deep learning enabled the automation ... This work centralizes to the creation of a multi-modal deep learning architecture for brain tumor classification that ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

Deep Learning (DL), particularly Convolutional Neural Networks ... In this work, a novel approach combining a transformerbased Swin-Unet architecture with seasonal synthesized spatiotemporal images ...