Zhang, David W.

17 publications

ICML 2024 CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen

ICLRW 2024 CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen

ICLR 2024 Graph Neural Networks for Learning Equivariant Representations of Neural Networks Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang

ICML 2024 Improved Generalization of Weight Space Networks via Augmentations Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

ICMLW 2024 Towards Bridging Classical and Neural Computation Through a Read-Eval-Print Loop David W. Zhang, Michaël Defferrard, Corrado Rainone, Roland Memisevic

ICLRW 2024 Towards Self-Improving Language Models for Code Generation Michaël Defferrard, Corrado Rainone, David W. Zhang, Blazej Manczak, Natasha Butt, Taco Cohen

ICMLW 2023 Latent Space Editing in Transformer-Based Flow Matching Vincent Tao Hu, David W Zhang, Meng Tang, Pascal Mettes, Deli Zhao, Cees G. M. Snoek

ICMLW 2023 Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks David W. Zhang, Miltiadis Kofinas, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Cees G. M. Snoek

ICLR 2023 Robust Scheduling with GFlowNets David W Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan

CVPR 2023 Self-Guided Diffusion Models Vincent Tao Hu, David W. Zhang, Yuki M. Asano, Gertjan J. Burghouts, Cees G. M. Snoek

ICML 2023 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

ICLR 2022 Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

LoG 2022 Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets David W Zhang, Gertjan J. Burghouts, Cees G. M. Snoek

NeurIPSW 2022 Self-Guided Diffusion Model Vincent Tao Hu, David W Zhang, Yuki M Asano, Gertjan J. Burghouts, Cees G. M. Snoek

NeurIPSW 2022 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

NeurIPSW 2022 Unlocking Slot Attention by Changing Optimal Transport Costs Yan Zhang, David W Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek

ICLR 2021 Set Prediction Without Imposing Structure as Conditional Density Estimation David W Zhang, Gertjan J. Burghouts, Cees G. M. Snoek