302 citations · 1k across the 48 of their papers we have counts for
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Visualizing the Effects of a Changing Distance on Data Using Continuous Embeddings
Gina Gruenhage, Manfred Opper, Simon Barthelme
Most Machine Learning (ML) methods, from clustering to classification, rely on a distance function to describe relationships between datapoints. For complex datasets it is hard to…
Temporal Autoencoding Improves Generative Models of Time Series
Chris Häusler, Alex Susemihl, Martin P Nawrot +1
Restricted Boltzmann Machines (RBMs) are generative models which can learn useful representations from samples of a dataset in an unsupervised fashion. They have been widely employ…
Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
Manfred Opper, Ulrich Paquet, Ole Winther
Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussi…