Amortised inference enables scalable learning of sequential latent-varia...
We address tracking and prediction of multiple moving objects in visual ...
Recently, it has been shown that many functions on sets can be represent...
We introduce a methodology for efficiently computing a lower bound to
em...
We introduce Deep Variational Bayes Filters (DVBF), a new method for
uns...
Approximate variational inference has shown to be a powerful tool for
mo...