| Diffusion models: A comprehensive survey of methods and applications L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, W Zhang, B Cui, ... ACM Computing Surveys 56 (4), 1-39, 2023 | 668 | 2023 |
| Dpgn: Distribution propagation graph network for few-shot learning L Yang, L Li, Z Zhang, X Zhou, E Zhou, Y Liu IEEE Conference on Computer Vision and Pattern Recognition, 13390-13399, 2020 | 241 | 2020 |
| Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion L Yang, S Hong International conference on machine learning, 25038-25054, 2022 | 85 | 2022 |
| Diffusion-based scene graph to image generation with masked contrastive pre-training L Yang, Z Huang, Y Song, S Hong, G Li, W Zhang, B Cui, B Ghanem, ... arXiv preprint arXiv:2211.11138, 2022 | 25 | 2022 |
| Omni-granular ego-semantic propagation for self-supervised graph representation learning L Yang, S Hong International Conference on Machine Learning, 25022-25037, 2022 | 13 | 2022 |
| Improving diffusion-based image synthesis with context prediction L Yang, J Liu, S Hong, Z Zhang, Z Huang, Z Cai, W Zhang, B Cui Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms L Yang, Z Yu, C Meng, M Xu, S Ermon, B Cui arXiv preprint arXiv:2401.11708, 2024 | 10 | 2024 |
| Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer W Zhang, L Yang, S Geng, S Hong IEEE Transactions on Neural Networks and Learning Systems, 2023 | 9* | 2023 |
| VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs L Yang, Y Tian, M Xu, Z Liu, S Hong, W Qu, W Zhang, B Cui, M Zhang, ... International Conference on Learning Representations, 2024 | 8* | 2024 |
| Realcompo: Dynamic equilibrium between realism and compositionality improves text-to-image diffusion models X Zhang, L Yang, Y Cai, Z Yu, J Xie, Y Tian, M Xu, Y Tang, Y Yang, B Cui arXiv preprint arXiv:2402.12908, 2024 | 4 | 2024 |
| Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing L Yang, Z Zhang, Z Yu, J Liu, M Xu, S Ermon, B Cui International Conference on Learning Representations, 2024 | 3 | 2024 |
| Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization L Yang, J Zheng, H Wang, Z Liu, Z Huang, S Hong, W Zhang, B Cui IEEE Transactions on Knowledge and Data Engineering, 2023 | 3 | 2023 |
| Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models Z Huang, L Yang, X Zhou, Z Zhang, W Zhang, X Zheng, J Chen, Y Wang, ... International Conference on Learning Representations, 2024 | 2 | 2024 |
| Retrieval-Augmented Generation for AI-Generated Content: A Survey P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu, L Yang, W Zhang, B Cui arXiv preprint arXiv:2402.19473, 2024 | 1 | 2024 |
| Structure-Guided Adversarial Training of Diffusion Models L Yang, H Qian, Z Zhang, J Liu, B Cui CVPR 2024, 2024 | 1 | 2024 |
| Binding-Adaptive Diffusion Models for Structure-Based Drug Design Z Huang, L Yang, Z Zhang, X Zhou, Y Bao, X Zheng, Y Yang, Y Wang, ... AAAI Conference on Artificial Intelligence, 2024 | | 2024 |
Bin CUIProfessor of Computer Science, Peking UniversityПотвърден имейл адрес: pku.edu.cn
