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pro vyhledávání: '"Lei, Huan"'
Autor:
Lyu, Liyao, Lei, Huan
One essential goal of constructing coarse-grained molecular dynamics (CGMD) models is to accurately predict non-equilibrium processes beyond the atomistic scale. While a CG model can be constructed by projecting the full dynamics onto a set of resolv
Externí odkaz:
http://arxiv.org/abs/2409.11519
Autor:
Lei, Chang, Lei, Huan
Artificial intelligence for card games has long been a popular topic in AI research. In recent years, complex card games like Mahjong and Texas Hold'em have been solved, with corresponding AI programs reaching the level of human experts. However, the
Externí odkaz:
http://arxiv.org/abs/2407.10279
Autor:
Lyu, Liyao, Lei, Huan
One essential problem in quantifying the collective behaviors of molecular systems lies in the accurate construction of free energy surfaces (FESs). The main challenges arise from the prevalence of energy barriers and the high dimensionality. Existin
Externí odkaz:
http://arxiv.org/abs/2311.05009
We present a data-driven method to learn stochastic reduced models of complex systems that retain a state-dependent memory beyond the standard generalized Langevin equation (GLE) with a homogeneous kernel. The constructed model naturally encodes the
Externí odkaz:
http://arxiv.org/abs/2310.18582
Automating the checkout process is important in smart retail, where users effortlessly pass products by hand through a camera, triggering automatic product detection, tracking, and counting. In this emerging area, due to the lack of annotated trainin
Externí odkaz:
http://arxiv.org/abs/2308.09708
Autor:
Lyu, Liyao, Lei, Huan
We introduce a machine-learning-based coarse-grained molecular dynamics (CGMD) model that faithfully retains the many-body nature of the inter-molecular dissipative interactions. Unlike common empirical CG models, the present model is constructed bas
Externí odkaz:
http://arxiv.org/abs/2304.09044
We consider a scenario where we have access to the target domain, but cannot afford on-the-fly training data annotation, and instead would like to construct an alternative training set from a large-scale data pool such that a competitive model can be
Externí odkaz:
http://arxiv.org/abs/2303.16186
Reconstructing 3D point clouds into triangle meshes is a key problem in computational geometry and surface reconstruction. Point cloud triangulation solves this problem by providing edge information to the input points. Since no vertex interpolation
Externí odkaz:
http://arxiv.org/abs/2301.09253
Autor:
Lei, Huan1,2,3 (AUTHOR), Yu, Xueqing1,2,3 (AUTHOR), Fan, Daidi1,2,3 (AUTHOR) fandaidi@nwu.edu.cn
Publikováno v:
Advanced Science. 11/13/2024, Vol. 11 Issue 42, p1-19. 19p.
A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and continuum scale. The multi-scale nature imposes a challenge to construct re
Externí odkaz:
http://arxiv.org/abs/2210.12482