Nature

Climate science data can be compressed efficiently by dual-stage extreme compression with a variational auto-encoder transformer

Climate change makes accurate weather prediction and large-scale data analysis increasingly crucial, but the sheer volume of weather data strains data storage and sharing. Here we introduce Aeolus, a ...
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 ...
IEEE

Resilient Collaborative Caching for Multi-Edge Systems With Robust Federated Deep Learning

Abstract: As a key technique for future networks, the performance of emerging multi-edge caching is often limited by inefficient collaboration among edge nodes and improper resource configuration.
IEEE

Robust Training of Vector Quantized Bottleneck Models

Abstract: In this paper we demonstrate methods for reliable and efficient training of discrete representation using Vector-Quantized Variational Auto-Encoder models (VQ-VAEs). Discrete latent variable ...
PNAS

Joint trajectory inference for single-cell genomics using deep learning with a mixture prior

We propose an approach for joint trajectory analysis of multiple single-cell sequencing data, combining Bayesian hierarchical models with variational autoencoders. Based on a coherent statistical ...
eLife

Disentangled multi-subject and social behavioral representations through a constrained subspace variational autoencoder (CS-VAE)

This paper is a valuable step in multi-subject behavioral modeling using an extension of the Variational Autoencoder (VAE) framework. Using a novel partition of the latent space and in tandem with a ...
Nature

A deep learning approach for morphological feature extraction based on variational auto-encoder: an application to mandible shape

Shape measurements are crucial for evolutionary and developmental biology; however, they present difficulties in the objective and automatic quantification of arbitrary shapes. Conventional approaches ...
VentureBeat

Two years after DALL-E debut, its inventor is "surprised" by impact

Since then, things have moved fast, according to OpenAI researcher, DALL-E inventor and DALL-E 2 co-inventor Aditya Ramesh. It's more than a bit of an understatement, given the dizzying pace of ...