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cs.LG2024
Disentangled Representation Learning with the Gromov-Monge Gap
Théo Uscidda, Luca Eyring, Karsten Roth +3
Learning disentangled representations from unlabelled data is a fundamental challenge in machine learning. Solving it may unlock other problems, such as generalization, interpretab…
cs.CV2024
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
Luca Eyring, Shyamgopal Karthik, Karsten Roth +2
Text-to-Image (T2I) models have made significant advancements in recent years, but they still struggle to accurately capture intricate details specified in complex compositional pr…