107 citations · 163 across the 13 of their papers we have counts for
5 papers · 1 filter
User-Dependent Neural Sequence Models for Continuous-Time Event Data
Alex Boyd, Robert Bamler, Stephan Mandt +1
Continuous-time event data are common in applications such as individual behavior data, financial transactions, and medical health records. Modeling such data can be very challengi…
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…
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…
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…
Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion
Fabian Jirasek, Rodrigo A. S. Alves, Julie Damay +6
Activity coefficients, which are a measure of the non-ideality of liquid mixtures, are a key property in chemical engineering with relevance to modeling chemical and phase equilibr…