Principal component analysis (PCA) is a standard dimensionality reductio...
Lipschitz regularized f-divergences are constructed by imposing a bound ...
We propose a new family of regularized Rényi divergences parametrized no...
We propose a novel variant of the multiplicative weights update method
w...
Inferring the driving equations of a dynamical system from population or...
We develop a general framework for constructing new information-theoreti...
The increased adoption of digital assistants makes text-to-speech (TTS)
...
Recent advancements in deep learning led to human-level performance in
s...
Variational representations of distances and divergences between
high-di...
Predictive modelling represents an emerging field that combines existing...
Despite the continuous improvements of Generative Adversarial Networks
(...
Compositional data consists of vectors of proportions whose components s...
The impressive success of Generative Adversarial Networks (GANs) is ofte...
Predictive modelling is a data-analysis task common in many scientific
f...