Peer-reviewed publications

Preprints, workshop papers, et cetera

  • Practical and Consistent Estimation of f-Divergences (2019) (arxiv)
  • An Empirical Study of Generative Models with Encoders (2018) (arxiv)
  • Wasserstein Auto-encoders: Latent Dimensionality and Random Encoders (ICLR workshop paper, 2018) (poster, paper)
  • Learning Disentangled Representations with Wasserstein Auto-Encoders (ICLR workshop paper, 2018) (poster, paper)
  • On the Latent Space of Wasserstein Auto-Encoders (2018) (arxiv)
  • Probabilistic Active Learning of Functions in Structural Causal Models (2017) (arxiv, workshop posterslides)
  • Masters thesis: Three Variable Kernel Independence Testing with Time Series (2015)
  • The VC-Dimension of Similarity Hypothesis Spaces (2015) (arxiv)

Some things I am interested in

  • Generative Modelling – Wasserstein Autoencoders, Variational Autoencoders and Generative Adversarial Networks
  • Kernel methods – applications of the kernel mean embedding
  • Causality
  • Gaussian Processes