7 citations · 12 across the 7 of their papers we have counts for
7 papers
E-CHUM: Event-based Cameras for Human Detection and Urban Monitoring
Jack Brady, Andrew Dailey, Kristen Schang +1
Understanding human movement and city dynamics has always been challenging. From traditional methods of manually observing the city's inhabitant, to using cameras, to now using sen…
Is Generation Required for Data-Efficient Perception?
Jack Brady, Bernhard Schölkopf, Thomas Kipf +2
It has been hypothesized that achieving the data efficiency of human visual perception requires a generative approach in which internal representations result from inverting a deco…
Interaction Asymmetry: A General Principle for Learning Composable Abstractions
Jack Brady, Julius von Kügelgen, Sébastien Lachapelle +3
Learning disentangled representations of concepts and re-composing them in unseen ways is crucial for generalizing to out-of-domain situations. However, the underlying properties o…
Provable Compositional Generalization for Object-Centric Learning
Thaddäus Wiedemer, Jack Brady, Alexander Panfilov +3
Learning representations that generalize to novel compositions of known concepts is crucial for bridging the gap between human and machine perception. One prominent effort is learn…
Provably Learning Object-Centric Representations
Jack Brady, Roland S. Zimmermann, Yash Sharma +3
Learning structured representations of the visual world in terms of objects promises to significantly improve the generalization abilities of current machine learning models. While…
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Patrik Reizinger, Luigi Gresele, Jack Brady +6
Variational autoencoders (VAEs) are a popular framework for modeling complex data distributions; they can be efficiently trained via variational inference by maximizing the evidenc…
Normalizing flows for microscopic many-body calculations: an application to the nuclear equation of state
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. We demonstrate that nor…