A machine learning system uses four wearable sensors to assess balance exercise difficulty and provide AI-driven feedback to ...

Current AI models fail to recognize 'relational' image similarities, such as how the Earth’s layers are similar to a peach, ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

Hindsight achieves 91.4% accuracy, validated by research with collaborators from the Washington Post and Virginia Tech ...

This special report introduces small area estimation as a modern approach for producing reliable, stand-level forest ...

Investigations suggest V2P may be efficiently applied for the automated identification of causal variants in simulated and actual patient sequencing data across phenotypes.

Shaping the direction of AI’s development cannot be the prerogative of engineers and CEOs alone. Citizens have a role not ...

In contrast to machine learning (ML), machine unlearning is the process of removing certain data or influences from models as ...

In the race to build increasingly autonomous AI agents, the community has focused heavily on improving agents’ capabilities ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...