Computational science articles from across Nature Portfolio

A recent study has modeled and quantified the expected rise in electronic waste due to the increasing deployment of generative artificial intelligence.

Quantum error mitigation improves the accuracy of quantum computers at a computational overhead. Liao et al. demonstrate that classical machine learning models can deliver accuracy comparable to that of conventional techniques while reducing quantum computational costs.

A recent study has modeled and quantified the expected rise in electronic waste due to the increasing deployment of generative artificial intelligence.

Nature Computational Science invites researchers to submit Correspondence pieces.

Active machine learning is employed in academia and industry to support drug discovery. A recent study unravels the factors that influence a deep learning models’ ability to guide iterative discovery.

Navigating built environments can be a challenge for persons with disabilities. Emerging computational capabilities are promising to help by providing the right information at the right time in accessible formats.

The widespread availability of digital traces capturing individuals’ daily mobility has the potential to enrich the understanding of the relationship between mobility, gender and socioeconomic factors. In fact, it has led to a heightened interest in deriving policy insights from these data. However, it is also essential to put the focus on methodological aspects to address the data gaps and biases.