Logic Tensor Network (LTN) is a Neural-Symbolic (NeSy) framework which supports learning of neural networks using the satisfaction of a first-order logic knowledge base as an objective. In other words ...

Abstract: Tensor decomposition has been demonstrated to be successful in a wide range of applications, from neuroscience and wireless communications to social networks. In an online setting, ...

Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China ...

Abstract: In this article, we propose a novel integrated sensing and communication (ISAC) algorithm for massive multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) ...

Artificial Intelligence (AI) has transformed how we interact with technology, but at its core, AI relies on a fundamental building block: tensors. Think of tensors as the unsung heroes that make data ...

Twenty years ago, Nvidia made a calculated decision to expand its focus from gaming to high-performance computing processing. So much of HPC is mathematics, and the GPU is, by design, a massive math ...

In the past few decades, multi-linear algebra also known as tensor algebra has been adapted and employed as a tool for various engineering applications. Recent developments in tensor algebra have ...

Spatially-resolved RNA profiling has now been widely used to understand cells’ structural organizations and functional roles in tissues, yet it is challenging to reconstruct the whole spatial ...

Tensor networks have been recognized as an effective representation and research tool for quantum systems. Tensor network-based algorithms are used to explore the basic properties of quantum systems.

Circuit design for quantum machine learning remains a formidable challenge. Inspired by the applications of tensor networks across different fields and their novel presence in the classical machine ...