1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Learning Disentangled Discrete Representations
David Friede, Christian Reimers, Heiner Stuckenschmidt +1
Recent successes in image generation, model-based reinforcement learning, and text-to-image generation have demonstrated the empirical advantages of discrete latent representations…
cs.CV2021★ 1 cited
Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing
Christian Reimers, Paul Bodesheim, Jakob Runge +1
Bias in classifiers is a severe issue of modern deep learning methods, especially for their application in safety- and security-critical areas. Often, the bias of a classifier is a…