technologynetworks

Multiomics Data Integration With Machine Learning: Methods, Tools, and Biological Applications

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...
technologynetworks

Single-Cell RNA-Seq Data Analysis With AI: Tools, Workflows, and Biological Interpretation

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...
IEEE

Quaternion Vector Quantized Variational Autoencoder

Abstract: Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in ...
Tech Xplore on MSN

Ferroelectric memory enables one chip to sample randomness and compute for generative AI

For the first time, a research team has demonstrated an artificial intelligence semiconductor technology that integrates the ...
IEEE

Low Latency Variational Autoencoder on FPGAs

Abstract: Variational Autoencoders (VAEs) are at the forefront of generative model research, combining probabilistic theory with neural networks to learn intricate data structures and synthesize ...