Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...
We consider matrix completion for recommender systems from the point of view of link prediction on graphs. Interaction data such as movie ratings can be represented by a bipartite user-item graph with ...
Recent methods generalize convolutional layers from Euclidean domains to graph-structured data by approximating the eigenbasis of the graph Laplacian. The computationally-efficient and broadly-used ...
A team at Stanford has shown that large language models can automatically generate highly efficient GPU kernels, sometimes outperforming the standard functions found in the popular machine learning ...
Abstract: Recently, deep learning methods have achieved superior performance for polarimetric synthetic aperture radar (PolSAR) image classification. Existing deep learning methods learn PolSAR data ...
Materials Research Laboratory, University of Illinois, Urbana, Illinois 61801, United States Department of Mechanical Science and Engineering, University of Illinois, Urbana, Illinois 61801, United ...
Spinal cord injury (SCI) may lead to impaired motor function, autonomic nervous system dysfunction, and other dysfunctions. Brain-computer Interface (BCI) system based on motor imagery (MI) can ...
Abstract: Due to the changeable, high-dimensional, nonstationary, and other characteristics of electroencephalography (EEG) signals, the recognition of EEG signals is mostly limited to independent ...
As the nuclear power plant containment is the third barrier to nuclear safety, real-time monitoring of containment leakage rate is very important in addition to the overall leakage test before an ...
TensorLy-Torch is a Python library for deep tensor networks that builds on top of TensorLy and PyTorch. It allows to easily leverage tensor methods in a deep learning setting and comes with all ...
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