关注
David W. Zhang
David W. Zhang
其他姓名David Zhang, Wei David Zhang
Research Scientist, FAIR, Meta
在 meta.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Robust Scheduling with GFlowNets
DW Zhang, C Rainone, M Peschl, R Bondesan
ICLR 2023 - International Conference on Learning Representations, 2023
492023
Self-Guided Diffusion Models
VT Hu*, DW Zhang*, YM Asano, GJ Burghouts, CGM Snoek
CVPR 2023 - Conference on Computer Vision and Pattern Recognition, 2023
362023
Graph Neural Networks for Learning Equivariant Representations of Neural Networks
M Kofinas*, B Knyazev, Y Zhang, Y Chen, GJ Burghouts, E Gavves, ...
ICLR 2024 - International Conference on Learning Representations, 2024
252024
Latent space editing in transformer-based flow matching
VT Hu, DW Zhang, P Mettes, M Tang, D Zhao, CGM Snoek
AAAI 2024 - Association for the Advancement of Artificial Intelligence, 2023
232023
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay
N Butt, B Manczak, A Wiggers, C Rainone, D Zhang, M Defferrard, ...
ICML 2024 - International Conference on Machine Learning, 2024
202024
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation
Y Zhang*, DW Zhang*, S Lacoste-Julien, GJ Burghouts, CGM Snoek
ICLR 2022 - International Conference on Learning Representations, 2022
202022
Set Prediction without Imposing Structure as Conditional Density Estimation
DW Zhang, GJ Burghouts, CGM Snoek
ICLR 2021 - International Conference on Learning Representations, 2021
152021
Improved Generalization of Weight Space Networks via Augmentations
A Shamsian, A Navon, DW Zhang, Y Zhang, E Fetaya, G Chechik, ...
ICML 2024 - International Conference on Machine Learning, 2024
82024
Unlocking Slot Attention by Changing Optimal Transport Costs
Y Zhang*, DW Zhang*, S Lacoste-Julien, GJ Burghouts, CGM Snoek
ICML 2023 - International Conference on Machine Learning, 2023
82023
Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets
DW Zhang, GJ Burghouts, CGM Snoek
LoG 2022 - Learning on Graphs Conference, 53: 1-53: 18, 2022
6*2022
Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks
DW Zhang, M Kofinas, Y Zhang, Y Chen, GJ Burghouts, CGM Snoek
2nd Annual Topology, Algebra, and Geometry in Machine Learning Workshop at ICML, 2023
42023
Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networks
S Wang, DW Zhang, JH Huang, S Rudinac, M Kackovic, N Wijnberg, ...
arXiv preprint arXiv:2405.13372, 2024
32024
Data Augmentations in Deep Weight Spaces
A Shamsian*, DW Zhang*, A Navon, Y Zhang, M Kofinas, I Achituve, ...
Symmetry and Geometry in Neural Representations Workshop at NeurIPS, 2023
22023
Towards Self-Improving Language Models for Code Generation
M Defferrard, C Rainone, DW Zhang, B Manczak, N Butt, T Cohen
Workshop on Large Language Model (LLM) Agents at ICLR 2024, 2024
2024
Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling
L Heuvel, G Burghouts, DW Zhang, G Englebienne, SB van Rooij
Workshop on Diffusion Models at NeurIPS, 2023
2023
Towards Bridging Classical and Neural Computation through a Read-Eval-Print Loop
DW Zhang, M Defferrard, C Rainone, R Memisevic
ICML 2024 Workshop on LLMs and Cognition, 0
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