Tech Xplore

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 ...
Scientific Research Publishing

Variational Auto-Encoder and Speeded-Up Robust Features Hybrid Model for Anomaly Detection and Localization in Video Sequence with Scale Variation ()

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...
IEEE

Distribution-Aware and Class-Adaptive Aggregation for Few-Shot Hyperspectral Image Classification

Abstract: Recently, few-shot learning based on meta-learning has shown great potential in hyperspectral image classification (HSIC) due to its excellent adaptability to limited training samples.
GitHub

RAVE: Realtime Audio Variational autoEncoder

Official implementation of RAVE: A variational autoencoder for fast and high-quality neural audio synthesis (article link) by Antoine Caillon and Philippe Esling. If you use RAVE as a part of a music ...
Nature

Hybrid feature engineering of medical data via variational autoencoders with triplet loss: a COVID-19 prognosis study

Medical machine learning frameworks have received much attention in recent years. The recent COVID-19 pandemic was also accompanied by a surge in proposed machine learning algorithms for tasks such as ...
PNAS

Robust probabilistic modeling for single-cell multimodal mosaic integration and imputation via scVAEIT

Single-cell multimodal assays provide an unprecedented opportunity for investigating heterogeneity of cell types and novel associations with disease and development. Although analyses of such ...
C&EN

Accurate Tumor Subtype Detection with Raman Spectroscopy via Variational Autoencoder and Machine Learning

State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, P.R. China State Key Laboratory of Oncogenes and Related Genes, ...
Frontiers

Explore Protein Conformational Space With Variational Autoencoder

Molecular dynamics (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational ...
eLife

Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires

Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, ...