Visual Studio Magazine

Generating Synthetic Data Using a Variational Autoencoder with PyTorch

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...
inc42

What Are Variational Autoencoders? Here’s All You Need to Know

Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder takes ...
VentureBeat

DeepMind makes big jump toward interpreting LLMs with sparse autoencoders

Large language models (LLMs) have made remarkable progress in recent years. But understanding how they work remains a challenge and scientists at artificial intelligence labs are trying to peer into ...
Visual Studio Magazine

Data Dimensionality Reduction Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...
ascopubs.org

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides.

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...