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Unlocking Slot Attention by Changing Optimal Transport Costs
Slot attention is a powerful method for objectcentric modeling in images and videos. However, its set-equivariance limits its ability …
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
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Self-Guided Diffusion Models
Diffusion models have demonstrated remarkable progress in image generation quality, especially when guidance is used to control the …
Vincent Tao Hu, David W. Zhang, Yuki M. Asano, Gertjan J. Burghouts, Cees G. M. Snoek
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Robust Scheduling with GFlowNets
Finding the best way to schedule operations in a computation graph is a classical NP-hard problem which is central to compiler …
David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan
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Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation
Most set prediction models in deep learning use set-equivariant operations, but they actually operate on multisets. We show that …
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek
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Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets
This paper aims for set-to-hypergraph prediction, where the goal is to infer the set of relations for a given set of entities. This is …
David W. Zhang, Gertjan J. Burghouts, Cees G. M. Snoek
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Set Prediction without Imposing Structure as Conditional Density Estimation
Set prediction is about learning to predict a collection of unordered variables with unknown interrelations. Training such models with …
David W. Zhang, Gertjan J. Burghouts, Cees G. M. Snoek
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