7 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
Graph Diffusion Transformers are In-Context Molecular Designers
Gang Liu, Jie Chen, Yihan Zhu +4
In-context learning allows large models to adapt to new tasks from a few demonstrations, but it has shown limited success in molecular design. Existing databases such as ChEMBL con…
cs.LG2025
Toward a Graph Foundation Model: Pre-Training Transformers With Random Walks
Ziyuan Tang, Jie Chen
A foundation model like GPT elicits many emergent abilities, owing to the pre-training with broad inclusion of data and the use of the powerful Transformer architecture. While foun…
stat.ML2022★ 7 cited
Neural Optimization Machine: A Neural Network Approach for Optimization
Jie Chen, Yongming Liu
A novel neural network (NN) approach is proposed for constrained optimization. The proposed method uses a specially designed NN architecture and training/optimization procedure cal…