no code implementations • 9 Oct 2023 • Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel
Learning representations that generalize to novel compositions of known concepts is crucial for bridging the gap between human and machine perception.
no code implementations • 23 May 2023 • Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
Under this generative process, we prove that the ground-truth object representations can be identified by an invertible and compositional inference model, even in the presence of dependencies between objects.
1 code implementation • 6 Jun 2022 • Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
Leveraging self-consistency, we show that the ELBO converges to a regularized log-likelihood.
no code implementations • 4 Feb 2021 • Jack Brady, Pengsheng Wen, Jeremy W. Holt
Normalizing flows are a class of machine learning models used to construct a complex distribution through a bijective mapping of a simple base distribution.
Nuclear Theory