Differentiable programming is a fresh programming paradigm which composes
parameterized algorithmic components and optimizes them using gradient search. The …

Successfully navigating a complex environment to obtain a desired outcome is a difficult
task, that up to recently was believed to be capable only by humans. This perception has …

We present a 3D capsule module for processing point clouds that is equivariant to 3D
rotations and translations, as well as invariant to permutations of the input points. The …

Characterizing the performance of noisy quantum circuits is central to the production of
prototype quantum computers and can enable improved quantum error correction that …

Hypernetworks are meta neural networks that generate weights for a main neural network in
an end-to-end differentiable manner. Despite extensive applications ranging from multi-task …

Computing derivatives of tensor expressions, also known as tensor calculus, is a
fundamental task in machine learning. A key concern is the efficiency of evaluating the …

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 …

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 …

Solving a linear system $ Ax= b $ is a fundamental scientific computing primitive for which
numerous solvers and preconditioners have been developed. These come with parameters …

Abstract Graph autoencoders (Graph-AEs) learn representations of given graphs by aiming
to accurately reconstruct them. A notable application of Graph-AEs is graph-level anomaly …