Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.
Hands on with GitHub’s open-source tool kit for steering AI coding agents by combining detailed specifications and a human in ...
Utah governor: 'We got him' Zoe Ball reflects on ‘uncomfortable’ lads’ mag shoots during her early career Billionaire’s water to be cut off after shipping in private supplies to fill his Wiltshire ...
Fork of cabinet decisions dataset for academic purposes. SE4050 Deep Learning Team Project - Comparative analysis of three unsupervised learning models (clustering, topic modeling, deep learning) o… ...
The quality of “Fritillariae Cirrhosae Bulbus (FCB)” is influenced by its geographical origin and cultivation management. Characterizing quality differences among FCB from different sources through ...
Copyright 2025 The Associated Press. All Rights Reserved. Copyright 2025 The Associated Press. All Rights Reserved. Nepal’s government responded to escalating ...
Abstract: This letter introduces a novel semantics-aware inspection planning policy derived through deep reinforcement learning. Reflecting the fact that within autonomous informative path planning ...
A high-performance, cross-platform process manager built in Rust, inspired by PM2 with innovative features that exceed the original. PMDaemon runs natively on Linux, Windows, and macOS and is designed ...
Abstract: This study investigates federated deep learning for multi-horizon indoor climate forecasting in historic buildings. Unlike traditional centralized or isolated local learning approaches, this ...
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