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David W. Zhang

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Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Mar 20, 2024
Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang

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Improved Generalization of Weight Space Networks via Augmentations

Feb 06, 2024
Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

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Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling

Dec 19, 2023
Leander van den Heuvel, Gertjan Burghouts, David W. Zhang, Gwenn Englebienne, Sabina B. van Rooij

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Data Augmentations in Deep Weight Spaces

Nov 15, 2023
Aviv Shamsian, David W. Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron

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Unlocking Slot Attention by Changing Optimal Transport Costs

Jan 30, 2023
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

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Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation

Nov 23, 2021
Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

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Recurrently Predicting Hypergraphs

Jun 26, 2021
David W. Zhang, Gertjan J. Burghouts, Cees G. M. Snoek

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Set Prediction without Imposing Structure as Conditional Density Estimation

Oct 08, 2020
David W. Zhang, Gertjan J. Burghouts, Cees G. M. Snoek

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