28 citations · 43 across the 5 of their papers we have counts for
6 papers
Quantifying Annotation Agreement in Object Detection with Optimal Transport
Kirill Prokhorov, Alexandr A. Kalinin
Reliable validation of machine learning models is a crucial step in designing robust and trustworthy systems. Yet validation relies on annotated test sets treated as ground truth,…
3D Molecular Representation Learning for Organic Mixtures: Viscosity and Density Prediction
Haicheng Qu, Yanyi Su, Ning Wang +4
The viscosity and density of organic mixtures are essential properties for designing lubricants, solvents, and heat transfer fluids. In engineering practice, formulating a function…
NMRPeak: a ready-to-use intelligent system for molecular structure elucidation enabled by synergistic cross-modal learning
Fanjie Xu, Jinyuan Hu, Jingxiang Zou +8
One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterizatio…
Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts
Fanjie Xu, Wentao Guo, Feng Wang +8
The study of structure-spectrum relationships is essential for spectral interpretation, impacting structural elucidation and material design. Predicting spectra from molecular stru…
Auto-resolving the atomic structure at van der Waals interfaces using a generative model
Wenqiang Huang, Yuchen Jin, Zhemin Li +12
The high-resolution visualization of atomic structures is significant for understanding the relationship between the microscopic configurations and macroscopic properties of materi…
Revealing the molecular structures of a-Al2O3(0001)-water interface by machine learning based computational vibrational spectroscopy
Xianglong Du, Weizhi Shao, Chenglong Bao +3
Solid-water interfaces are crucial to many physical and chemical processes and are extensively studied using surface-specific sum-frequency generation (SFG) spectroscopy. To establ…