3 citations · 6 across the 5 of their papers we have counts for
5 papers
2DNMRGym: An Annotated Experimental Dataset for Atom-Level Molecular Representation Learning in 2D NMR via Surrogate Supervision
Yunrui Li, Hao Xu, Pengyu Hong
Two-dimensional (2D) Nuclear Magnetic Resonance (NMR) spectroscopy, particularly Heteronuclear Single Quantum Coherence (HSQC) spectroscopy, plays a critical role in elucidating mo…
Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics
Phu N. Tran, Sattvic Ray, Linnea Lemma +6
Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks. It uses those features to estimate the inter-frame motio…
TransPeakNet: Solvent-Aware 2D NMR Prediction via Multi-Task Pre-Training and Unsupervised Learning
Yunrui Li, Hao Xu, Ambrish Kumar +4
Nuclear Magnetic Resonance (NMR) spectroscopy is essential for revealing molecular structure, electronic environment, and dynamics. Accurate NMR shift prediction allows researchers…
Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning
Yifei Wang, Yunrui Li, Lin Liu +2
The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective…
A Machine Learning Approach to Robustly Determine Director Fields and Analyze Defects in Active Nematics
Yunrui Li, Zahra Zarei, Phu N. Tran +5
Active nematics are dense systems of rodlike particles that consume energy to drive motion at the level of the individual particles. They exist in natural systems like biological t…