To learn how cognition is implemented in the brain, we must build computational models
that can perform cognitive tasks, and test such models with brain and behavioral …

The world contains not only objects and features (red apples, glass bowls, wooden tables),
but also relations holding between them (apples contained in bowls, bowls supported by …

Large language models (LLMs) have been transformative. They are pretrained foundational
models that are self-supervised and can be adapted with fine-tuning to a wide range of …

Human commonsense understanding of the physical and social world is organized around
intuitive theories. These theories support making causal and moral judgments. When …

The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …

How does language inform our downstream thinking? In particular, how do humans make
meaning from language--and how can we leverage a theory of linguistic meaning to build …

Common-sense physical reasoning is an essential ingredient for any intelligent agent
operating in the real-world. For example, it can be used to simulate the environment, or to …

Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

Infants understand that people pursue goals, but how do they learn which goals people
prefer? We tested whether infants solve this problem by inverting a mental model of action …

A Bayesian framework helps address, in computational terms, what knowledge children start
with and how they construct and adapt models of the world during childhood. Within this …