We're surrounded by machines that talk to us, and we're talking back more than ever. Synthetic voices have moved beyond novelty into everyday tools: podcast narration, virtual coaching apps, and car ...

A collaborative research team led by Professor Pan Feng from the School of New Materials at Peking University Shenzhen Graduate School has developed a topology-based variational autoencoder framework ...

Ionic liquids (ILs) are a class of molten salts with a collection of exciting properties, which have been employed for wide-ranging applications across chemistry, biology, and materials science.

We conclude that sequence action representations contextually differentiate during early skill learning, an issue relevant to brain-computer interface applications in neurorehabilitation. Introduction ...

🎯 Objective This project explores the idea of using an AutoEncoder (AE) to compress pressure mat data into dense latent variables, and then build a separate model to predict the latent representation ...

Article citations More>> Tschannen, M., Bachem, O. and Lucic, M. (2018) Recent Advances in Autoencoder-based Representation Learning. arXiv: 1812.05069. has been cited by the following article: TITLE: ...

In this work, a new causal representation method based on a Graph autoencoder embedded AutoEncoder, named GeAE, is introduced to learn invariant representations across domains. The proposed approach ...