With growing populations and pressing environmental problems, future economies will be
increasingly plant-based. Now is the time to reimagine plant science as a critical component …

A central goal of artificial intelligence in high-stakes decision-making applications is to
design a single algorithm that simultaneously expresses generalizability by learning …

The processes underwriting the acquisition of culture remain unclear. How are shared
habits, norms, and expectations learned and maintained with precision and reliability across …

In addition to synthetic and semisynthetic compounds, natural products have received much
attention as prolific sources of lead compounds with therapeutic effects on various diseases …

We introduce a new class of time-continuous recurrent neural network models. Instead of
declaring a learning system's dynamics by implicit nonlinearities, we construct networks of …

Autonomous robots can learn to perform visual navigation tasks from offline human
demonstrations and generalize well to online and unseen scenarios within the same …

Nervous systems have evolved to combine environmental information with internal state to
select and generate adaptive behavioral sequences. To better understand these …

Imitation learning enables high-fidelity, vision-based learning of policies within rich,
photorealistic environments. However, such techniques often rely on traditional discrete-time …

There are easier things to make than a brain. Driven by the promise and resources of
biomedical research, developmental neurobiologists are trying to understand how it is done …

Computational models are powerful tools for exploring the properties of complex biological
systems. In neuroscience, data-driven models of neural circuits that span multiple scales are …