The design of neural network layers plays a crucial role in determining the efficiency and
performance of various computer vision tasks. However, most existing layers compromise …

ABSTRACT SQL is the standard language for retrieving and manipulating relational data.
Although SQL is ubiquitous for simple analytical queries, it is rarely used for more complex …

We consider the question: what is the abstraction that should be implemented by the
computational engine of a machine learning system? Current machine learning systems …

In this work, we propose a unified abstraction for graph algorithms: the Extended General
Einsums language, or EDGE. The EDGE language expresses graph algorithms in the …

The use of reconfigurable intelligent surfaces (RIS) can improve wireless communication by
modifying the wireless link to create virtual line-of-sight links, bypass blockages, suppress …

Biomathematics is an interdisciplinary subject consisting of mathematics and biology, which
is widely applicable for the analysis of biological problems. In this paper, we provide a …

The success of deep learning models on structured data has generated significant interest in
extending their application to non-Euclidean domains. In this work, we introduce a novel …

Capsule neural networks replace simple, scalar-valued neurons with vector-valued
capsules. They are motivated by the pattern recognition system in the human brain, where …

Bivariate partial information decompositions (PIDs) characterize how the information in a"
message" random variable is decomposed between two" constituent" random variables in …

Although optimization is the longstanding, algorithmic backbone of machine learning new
models still require the time-consuming implementation of new solvers. As a result, there are …