23 citations · 42 across the 13 of their papers we have counts for
3 papers · 1 filter
Trustworthy Machine Learning
Bálint Mucsányi, Michael Kirchhof, Elisa Nguyen +2
As machine learning technology gets applied to actual products and solutions, new challenges have emerged. Models unexpectedly fail to generalize to small changes in the distributi…
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates
Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh +1
Representation learning has significantly driven the field to develop pretrained models that can act as a valuable starting point when transferring to new datasets. With the rising…
Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs
Michael Kirchhof, Enkelejda Kasneci, Seong Joon Oh
Contrastively trained encoders have recently been proven to invert the data-generating process: they encode each input, e.g., an image, into the true latent vector that generated t…