Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

Many research questions in Earth and environmental sciences are inherently causal,
requiring robust analyses to establish whether and how changes in one variable cause …

Abstract Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode
model equations, like Partial Differential Equations (PDE), as a component of the neural …

Where Medical Statistics Meets Artificial Intelligence | New England Journal of Medicine Skip to
main content The New England Journal of Medicine homepage Advanced Search SEARCH …

Abstract Machine-learning models for medical tasks can match or surpass the performance
of clinical experts. However, in settings differing from those of the training dataset, the …

Traditional machine learning paradigms are based on the assumption that both training and
test data follow the same statistical pattern, which is mathematically referred to as …

Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might
improve research. Why are AI tools so attractive and what are the risks of implementing them …

Generalization to out-of-distribution (OOD) data is a capability natural to humans yet
challenging for machines to reproduce. This is because most learning algorithms strongly …

The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

Abstract Domain generalization (DG) is essentially an out-of-distribution problem, aiming to
generalize the knowledge learned from multiple source domains to an unseen target …