Hypothesis: The primary objective of this study is to develop an end-to-end deep learning framework based on multi-task learning to predict pulmonary nodule growth by jointly modeling nodule ...

Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out.

Get festive! Watch Gabi's-Vintage transform her hair into a 1960s-inspired Christmas tree using the Wavytalk Multi Curl. A fun and creative holiday hairstyle! Passenger who died on cruise ship was ...

Abstract: Multi-task multi-agent reinforcement learning (M T-MARL) has recently gained attention for its potential to enhance MARL's adaptability across multiple tasks. However, it is challenging for ...

The FBI Anchorage Field Office is participating in the first-of-its-kind Homeland Security Task Force (HSTF), which coordinates law enforcement efforts nationwide to crush violent crime. The FBI and ...

Abstract: Multi-task representation learning is an emerging machine learning paradigm that integrates data from multiple sources, harnessing task similarities to enhance overall model performance. The ...

This repository is still under development and may contain bugs or incomplete features. It is intended for research purposes and not for production use. StockFormer.py Main model implementation ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A few public databases provide biological activity data for ...

As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...