103 citations · 193 across the 10 of their papers we have counts for
3 papers · 1 filter
Probing the Robustness of Independent Mechanism Analysis for Representation Learning
Joanna Sliwa, Shubhangi Ghosh, Vincent Stimper +2
One aim of representation learning is to recover the original latent code that generated the data, a task which requires additional information or inductive biases. A recently prop…
Resampling Base Distributions of Normalizing Flows
Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato
Normalizing flows are a popular class of models for approximating probability distributions. However, their invertible nature limits their ability to model target distributions who…
Independent mechanism analysis, a new concept?
Luigi Gresele, Julius von Kügelgen, Vincent Stimper +2
Independent component analysis provides a principled framework for unsupervised representation learning, with solid theory on the identifiability of the latent code that generated…