Artificial intelligence (AI) has been transforming the practice of drug discovery in the past
decade. Various AI techniques have been used in many drug discovery applications, such …

Given access to accurate solutions of the many-electron Schrödinger equation, nearly all
chemistry could be derived from first principles. Exact wave functions of interesting chemical …

Automatic Chemical Design is a framework for generating novel molecules with optimized
properties. The original scheme, featuring Bayesian optimization over the latent space of a …

Recently developed methods in computational neuroethology have enabled increasingly
detailed and comprehensive quantification of animal movements and behavioral kinematics …

For large-scale in-service electric vehicles (EVs) that undergo potential maintenance,
second-hand transactions, and retirement, it is crucial to rapidly evaluate the health status of …

We design a neural network Ansatz for variationally finding the ground-state wave function
of the homogeneous electron gas, a fundamental model in the physics of extended systems …

Deep neural networks have been successfully applied to medical image analysis tasks like
segmentation and synthesis. However, even if a network is trained on a large dataset from …

Abstract The rise of Federated Learning (FL) is bringing machine learning to edge
computing by utilizing data scattered across edge devices. However, the heterogeneity of …

Understanding superfluidity remains a major goal of condensed matter physics. Here, we
tackle this challenge utilizing the recently developed fermionic neural network (FermiNet) …

As population genetic data increase in size, new methods have been developed to store
genetic information in efficient ways, such as tree sequences. These data structures are …