SMPTE has released an updated engineering report examining artificial intelligence and machine learning in media ... Read More ...
Quantum Variational Graph Auto-Encoders (QVGAE) represent an integration of graph-based machine learning and quantum computing. In this work, we propose a first-of-its-kind quantum implementation of ...
A team of researchers have developed a domain adaption framework capable of transferring knowledge from solar power plants with abundant data to plants that need to be trained without labelled data.
We present a novel neural network (NN) method for the detection and removal of radio frequency interference (RFI) from the raw digitized signal in the signal processing chain of a typical radio ...
Abstract: Federated learning (FL) enables distributed joint training of machine learning (ML) models without the need to share local data. FL is, however, not immune to privacy threats such as model ...
Single-cell sequencing may be more specific than bulk sequencing but comes with a significant cost. At FoG Live: Single Cell and Spatial, we were joined by Jun Ding (McGill University) who discussed ...
We present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational ...
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