The field of natural language processing has seen impressive progress in recent years, with
neural network models replacing many of the traditional systems. A plethora of new models …

This survey presents the most relevant neural network models of autism spectrum disorder
and schizophrenia, from the first connectionist models to recent deep neural network …

Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

An introduction to a broad range of topics in deep learning, covering mathematical and
conceptual background, deep learning techniques used in industry, and research …

Inventors have long dreamed of creating machines that think. Ancient Greek myths tell of
intelligent objects, such as animated statues of human beings and tables that arrive full of …

Deep learning subsumes algorithms that automatically learn compositional representations.
The ability of these models to generalize well has ushered in tremendous advances in many …

Theoretical results suggest that in order to learn the kind of complicated functions that can
represent high-level abstractions (eg, in vision, language, and other AI-level tasks), one may …

A goal of statistical language modeling is to learn the joint probability function of sequences
of words in a language. This is intrinsically difficult because of the curse of dimensionality: a …

Optimality Theory first gained wide exposure from a course taught by Prince and Smolensky
at the 1991 Summer Institute of the Linguistic Society of America. The earliest and still the …

This paper describes a data organization system and genuine content-addressable memory
called the WEBSOM. It is a two-layer self-organizing map (SOM) architecture where …