Fabian Falck

Fabian Falck

Probabilistic deep learning, Deep generative models, VAEs, Causal inference

I am a PhD student at the University of Oxford, supervised by Chris Holmes. I am interested in probabilistic deep learning for topics in unsupervised learning and causal inference. Recently, I have worked on multi-facet clustering with variational autoencoders and matching for treatment effect estimation in causal inference.

Before joining Oxford, I obtained an MSc in Computer Science at Imperial College London, and an MSc in Industrial Engineering at Karlsruhe Institute of Technology, with visits at Shanghai’s Jiao Tong University, Tsinghua University in Beijing, Singapore and Carnegie Mellon University in the US. I later worked on research in computer vision, robotics and machine learning for health at Imperial and Carnegie Mellon.

Publications

2021

  • F. Falck , H. Zhang , M. Willetts , G. Nicholson , C. Yau , C. Holmes , Multi-Facet Clustering Variational Autoencoders, Advances in Neural Information Processing Systems, 2021.