Conference Papers

• [C10] A Denoising Pre-training Framework for Accelerating Novel Material Discovery.
  Shuaike Shen*, Ke Liu* ✉, Muzhi Zhu, Hao Chen
  Proc. Annual AAAI Conference on Artificial Intelligence. (AAAI'25)
  [code] [To appear] [Project Page]
• [C9] KA2ER: Knowledge Adaptive Amalgamation of ExpeRts for Medical Images Segmentation.
  Shangde Gao, Yichao Fu, Ke Liu, Hongxia Xu, Jian Wu
  Proc. International Conference on Medical Image Computing and Computing Assisted Intervention (MICCAI'24), CARE challenge, 2024.
  [code] [paper] [bib] [Project Page]
• [C8] Boost Your Crystal Model with Denoising Pre-training.
  Shuaike Shen*, Ke Liu*, Muzhi Zhu, Hao Chen
  Proc. International Conference on Machine Learning (ICML'24) AI4Science Workshop, 2024.
  [code] [paper] [bib] [Project Page]
• [C7] Floating Anchor Diffusion Model for Multi-motif Scaffolding.
  Ke Liu, Shuaike Shen, Weian Mao, Xiaoran Jiao, Zheng Sun, Hao Chen, Chunhua Shen
  Proc. International Conference on Machine Learning (ICML'24), 2024.
  [code] [paper] [bib] [Project Page]
• [C6] Contrastive Knowledge Amalgamation for Unsupervised Image Classification.
  Shangde Gao*, Yichao Fu*, Ke Liu*, Yuqiang Han.
  Proc. International Conference on Artificial Neural Networks (ICANN'23) 2023.
  (Oral presentation)
• [C5] Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling.
  Bei Yang, Jie Gu, Ke Liu, Xiaoxiao Xu, Rux Xu, Hong Liu, Huan Xu
  Proc. Knowledge Discovery and Data Mining (SIGKDD'23). 2023.
• [C4] Group Equivariant Vision Transformer.
  Rux Xu*, Kaifan Yang*, Ke Liu*✉, Fengxiang He.
  Proc. Conference on Uncertainty in Artificial Intelligence (UAI'23), 2023.
  [code] [paper] [bib]
• [C3] PCVAE: a Physics-Informed Neural Network for Determining the Symmetry and Geometry of Crystals.
  Ke Liu, Shangde Gao, Kaifan Yang, Yuqiang Han.
  Proc. International Joint Conference on Neural Networks (IJCNN'23) 2023.
  (Oral presentation)
  [code] [paper] [bib]
• [C2] Learning Interest-oriented Universal User Representation via Self-supervision.
  Qinghui Sun, Jie Gu, Xiaoxiao Xu, Rux Xu, Ke Liu, Bei Yang, Hong Liu, huan xu.
  Proc. International Conference on Multimedia (MM'22), 2022.
  [paper]
• [C1] S2SNet: A Pretrained Neural Network for Superconductivity Discovery.
  Ke Liu, Kaifan Yang, Jiahong Zhang, Rux Xu.
  Proc. International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.
  [code] [paper] [bib]

Journal Papers

• [J1] A Deep-Learning Approach for Low-Spatial-Coherence Imaging in Computer-Generated Holography.
  Xin Tong, Rux Xu, Ke Liu, Liangliang Zhao, Weilai Zhu, Daomu Zhao.
  Advanced Photonics Research.
  [paper] [code] [bib]
• [J2] Low-Data Drug Design with Few-Shot Generative Domain Adaptation.
  Ke Liu, Yuqiang Han, Zhichen Gong, Hongxia Xu.
  BioEngineering.
• [J3] Collaborative knowledge amalgamation: Preserving discriminability and transferability in unsupervised learning.
  Shangde Gao*, Yichao Fu*, Ke Liu*, Wei Gao, Hongxia Xu, Jian Wu, Yuqiang Han.
  Information Sciences.
• [J4] A periodicity aware transformer for crystal property prediction.
  Ke Liu, Kaifan Yang, Shangde Gao.
  Neural Computing and Applications.