64 citations · 113 across the 8 of their papers we have counts for
8 papers
Molecular dynamics-driven global tetra-atomic potential energy surfaces: Application to the AlF dimer
Xiangyue Liu, Weiqi Wang, Jesús Pérez-Ríos
In this work, we present a general machine learning approach for full-dimensional potential energy surfaces for tetra-atomic systems. Our method employs an active learning scheme t…
Sobolev Training for Implicit Neural Representations with Approximated Image Derivatives
Wentao Yuan, Qingtian Zhu, Xiangyue Liu +3
Recently, Implicit Neural Representations (INRs) parameterized by neural networks have emerged as a powerful and promising tool to represent different kinds of signals due to its c…
KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view Stereo
Yikang Ding, Qingtian Zhu, Xiangyue Liu +3
Supervised multi-view stereo (MVS) methods have achieved remarkable progress in terms of reconstruction quality, but suffer from the challenge of collecting large-scale ground-trut…
The chemistry of AlF and CaF production in buffer gas sources
X. Liu, W. Wang, S. C. Wright +4
In this work, we explore the role of chemical reactions on the properties of buffer gas-cooled molecular beams. In particular, we focus on scenarios relevant to the formation of Al…
TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers
Yikang Ding, Wentao Yuan, Qingtian Zhu +4
In this paper, we present TransMVSNet, based on our exploration of feature matching in multi-view stereo (MVS). We analogize MVS back to its nature of a feature matching task and t…
A data-driven approach to determine dipole moments of diatomic molecules
Xiangyue Liu, Gerard Meijer, Jesús Pérez-Ríos
We present a data-driven approach for the prediction of the electric dipole moment of diatomic molecules, which is one of the most relevant molecular properties. In particular, we…
On the universality of spectroscopic constants of diatomic molecules
Xiangyue Liu, Gerard Meijer, Jesús Pérez-Ríos
We show, through a machine learning approach, that the equilibrium distance, harmonic vibrational frequency, and binding energy of diatomic molecules are universally related. In pa…
NOMAD 2018 Kaggle Competition: Solving Materials Science Challenges Through Crowd Sourcing
Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto +7
Machine learning (ML) is increasingly used in the field of materials science, where statistical estimates of computed properties are employed to rapidly examine the chemical space…