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 ...
GitHub

Deep count autoencoder for denoising scRNA-seq data

A deep count autoencoder network to denoise scRNA-seq data and remove the dropout effect by taking the count structure, overdispersed nature and sparsity of the data into account using a deep ...
IEEE

Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach

Abstract: Human behavior prediction models enable robots to anticipate how humans may react to their actions, and hence are instrumental to devising safe and proactive robot planning algorithms.
Frontiers

Using Dimensionality Reduction and Clustering Techniques to Classify Space Plasma Regimes

Collisionless space plasma environments are typically characterized by distinct particle populations. Although moments of their velocity distribution functions help in distinguishing different plasma ...
IEEE

FragNet: Writer Identification Using Deep Fragment Networks

Abstract: Writer identification based on a small amount of text is a challenging problem. In this paper, we propose a new benchmark study for writer identification based on word or text block images ...