Storyboard of WCE Video Extraction Based on Frame difference. - Yanan Fu; Mrinal Mandal 001; David W. Zhang; Max Q.-H. Meng (Int. J. Inf. Acquis., 2011)

3-D shape recovery of luminal wall from WCE image. - Yanan Fu; David W. Zhang; Haiying Liu; Max Q.-H. Meng (ICAL, 2012)

Motion blur removal for humanoid robots. - Teng Li 005; David W. Zhang; Yanan Fu; Max Q.-H. Meng (ICAL, 2012)

Set Prediction without Imposing Structure as Conditional Density Estimation. - David W. Zhang; Gertjan J. Burghouts; Cees G. M. Snoek (ICLR, 2021)

Recurrently Predicting Hypergraphs. - David W. Zhang; Gertjan J. Burghouts; Cees G. M. Snoek (CoRR, 2021)

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

Pruning Edges and Gradients to Learn Hypergraphs From Larger Sets. - David W. Zhang; Gertjan J. Burghouts; Cees G. M. Snoek (LoG, 2022)

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

Robust Scheduling with GFlowNets. - David W. Zhang; Corrado Rainone; Markus Peschl; Roberto Bondesan (ICLR, 2023)

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

Data Augmentations in Deep Weight Spaces. - 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; et al. (CoRR, 2023)

Latent Space Editing in Transformer-Based Flow Matching. - Vincent Tao Hu; David W. Zhang; Pascal Mettes; Meng Tang 001; Deli Zhao; Cees G. M. Snoek (CoRR, 2023)

Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling. - Leander van den Heuvel; Gertjan J. Burghouts; David W. Zhang; Gwenn Englebienne; Sabina B. van Rooij (CoRR, 2023)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks. - Miltiadis Kofinas; Boris Knyazev 001; Yan Zhang; Yunlu Chen; Gertjan J. Burghouts; Efstratios Gavves; Cees G. M. Snoek; David W. Zhang (ICLR, 2024)

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

Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networks. - Shuai Wang 054; David W. Zhang; Jia-Hong Huang; Stevan Rudinac; Monika Kackovic; Nachoem Wijnberg; Marcel Worring (CoRR, 2024)

CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks. - Miltiadis Kofinas; Boris Knyazev 001; Yan Zhang; Yunlu Chen; Gertjan J. Burghouts; Efstratios Gavves; Cees Snoek; David W. Zhang (Zenodo, 2024)

Soft Policy Optimization: Online Off-Policy RL for Sequence Models. - Taco Cohen; David W. Zhang; Kunhao Zheng; Yunhao Tang; Rémi Munos; Gabriel Synnaeve (CoRR, 2025)

RL-finetuning LLMs from on- and off-policy data with a single algorithm. - Yunhao Tang; Taco Cohen; David W. Zhang; Michal Valko; Rémi Munos (CoRR, 2025)