57 citations · 140 across the 8 of their papers we have counts for
3 papers · 1 filter
Sinkhorn AutoEncoders
Giorgio Patrini, Rianne van den Berg, Patrick Forré +5
Optimal transport offers an alternative to maximum likelihood for learning generative autoencoding models. We show that minimizing the p-Wasserstein distance between the generator…
Explorations in Homeomorphic Variational Auto-Encoding
Luca Falorsi, Pim de Haan, Tim R. Davidson +4
The manifold hypothesis states that many kinds of high-dimensional data are concentrated near a low-dimensional manifold. If the topology of this data manifold is non-trivial, a co…
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders
Patrick Forré, Joris M. Mooij
We address the problem of causal discovery from data, making use of the recently proposed causal modeling framework of modular structural causal models (mSCM) to handle cycles, lat…