9 citations · 30 across the 8 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
eess.IV2020
Improving Inference for Neural Image Compression
Yibo Yang, Robert Bamler, Stephan Mandt
We consider the problem of lossy image compression with deep latent variable models. State-of-the-art methods build on hierarchical variational autoencoders (VAEs) and learn infere…
stat.ML2020★ 7 cited
Extreme Classification via Adversarial Softmax Approximation
Robert Bamler, Stephan Mandt
Training a classifier over a large number of classes, known as 'extreme classification', has become a topic of major interest with applications in technology, science, and e-commer…
eess.IV2020
Variational Bayesian Quantization
Yibo Yang, Robert Bamler, Stephan Mandt
We propose a novel algorithm for quantizing continuous latent representations in trained models. Our approach applies to deep probabilistic models, such as variational autoencoders…