47 citations · 47 across the 6 of their papers we have counts for
6 papers
ADMET-EvO: a self-evolving scientific agent for sustained research across heterogeneous tasks
Yiling Zhou, Yilin Wang, Jianmin Wang +8
Scientific agents can move beyond automated model building by using accumulated evidence to revise both their questions and experimental strategies. The challenge is sustaining thi…
Navigating committor landscape of biomolecules with a general pairwise interaction model
Jintu Zhang, Zichang Jin, Huifeng Zhao +5
Sampling rare conformation transitions between metastable states is a central challenge in atomistic simulations. While the committor function serve as an ideal reaction coordinate…
SelfTICA: contrastive learning of dynamical representations for rare-event sampling and characterization
Kai Zhu, Jintu Zhang, Pietro Novelli +2
Rare events govern many important molecular processes but remain difficult to characterize within accessible simulation timescales. This challenge has motivated machine-learning me…
Committors without Descriptors
Peilin Kang, Jintu Zhang, Enrico Trizio +2
The study of rare events is one of the major challenges in atomistic simulations, and several enhanced sampling methods towards its solution have been proposed. Recently, it has be…
Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
Kai Zhu, Enrico Trizio, Jintu Zhang +4
Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constraine…
A Scalable and Quantum-Accurate Foundation Model for Biomolecular Force Field via Linearly Tensorized Quadrangle Attention
Qun Su, Kai Zhu, Qiaolin Gou +11
Accurate atomistic biomolecular simulations are vital for disease mechanism understanding, drug discovery, and biomaterial design, but existing simulation methods exhibit significa…