Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Molecular docking predicts whether and how small molecules bind to a macromolecular
target using a suitable 3D structure. Scoring functions for structure‐based virtual screening …

Meta-learning, or learning to learn, is the science of systematically observing how different
machine learning approaches perform on a wide range of learning tasks, and then learning …

Rotating machinery intelligent diagnosis with large data has been researched
comprehensively, while there is still a gap between the existing diagnostic model and the …

Meta-learning, or learning to learn, is the science of systematically observing how different
machine learning approaches perform on a wide range of learning tasks, and then learning …

In high dimensions, most machine learning methods are brittle to even a small fraction of
structured outliers. To address this, we introduce a new meta-algorithm that can take in a …

The bioactivity of compounds plays an important role in drug development and discovery.
Existing machine learning approaches have poor generalizability in bioactivity prediction …

Empirical risk minimization (ERM) is typically designed to perform well on the average loss,
which can result in estimators that are sensitive to outliers, generalize poorly, or treat …

Molecular docking can be used to predict how strongly small‐molecule binders and their
chemical derivatives bind to a macromolecular target using its available three‐dimensional …

Computers can already be programmed for superhuman pattern recognition of images and
text. For machines to discover novel molecules, they must first be trained to sort through the …