Because the truth is: Yes, students are using A.I. And no, they’re not just using it to cheat. They’re using it to brainstorm ...

These three models form a variational autoencoder and can be trained jointly in a semi-supervised manner. The experimental results show that the regularization of the classification model based on the ...

A deep generative model based on a variational autoencoder (VAE), conditioned simultaneously by two target properties, is developed to inverse design stable magnetic materials. The structure of the ...

Built on Deep Research and Data Motorica’s technology is rooted in breakthrough academic work by co-founders Gustav Henter and Simon Alexanderson, who developed the world’s first deep generative model ...

Generative Adversarial Networks and Variational Autoencoders: Strategies for Materials Design A reoccurring challenge for materials discovery using GMs (and many other ML models) is the choice of ...

Finding target molecules with specific chemical properties plays a decisive role in drug development. We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for ...