no code implementations • 3 Nov 2017 • Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
Neural samplers such as variational autoencoders (VAEs) or generative adversarial networks (GANs) approximate distributions by transforming samples from a simple random source---the latent space---to samples from a more complex distribution represented by a dataset.
no code implementations • NeurIPS 2014 • Maximilian Nickel, Xueyan Jiang, Volker Tresp
Tensor factorizations have become popular methods for learning from multi-relational data.