supported by the National Natural Science Foundation of China(Grant Nos.62141214 and 62272171).
Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which ignores the distinct impacts from different neighbors when aggregating their features to update a node’s representation....
supported by the National Key R&D Program of China(Nos.2020YFA0713601 and 2023YFA1008800);the National Natural Science Foundation of China(Nos.22341304,22341303,22103079 and 22073092);the Cooperation Project between Jilin Province and CAS(No.2023SYHZ0003).
Using molecular dynamics(MD)simulations,this study explores the fluid properties of three polymer melts with the same number of entanglements,Z,achieved by adjusting the entanglement length Ne,while investigating the ...
supported by the National Key Research and Development Program (Grant No.2022YFC2405600);the National Natural Science Foundation of China (Grant No.61825601);the National Science Foundation of Jiangsu Province (Grant No.BK20192004B)。
Disentangling facial expressions from other disturbing facial attributes in face images is an essential topic for facial expression recognition.Previous methods only care about facial expression disentanglement(FED)it...
financially supported by the National Key R&D Program of China (2022YFA1503503 and 2022YFA1503504);the Natural Science Foundation of China (22038003,22178100,22178101 and 22008066);the Innovation Program of Shanghai Municipal Education Commission,the Program of Shanghai Academic/Technology Research Leader (21XD1421000);the Shanghai Science and Technology Innovation Action Plan (22JC1403800).
Tailoring the electronic metal-support interaction(EMSI)has attracted considerable interests as one of the most efficient approaches to improve both the activity and stability of metal catalysts in heterogeneous catal...
Edith Cowan University(ECU),Australia and Higher Education Commission(HEC)Pakistan,The Islamia University of Bahawalpur(IUB)Pakistan(5-1/HRD/UE STPI(Batch-V)/1182/2017/HEC).
The capability of Convolutional Neural Networks(CNNs)for sparse representation has significant application to complex tasks like Representation Learning(RL).However,labelled datasets of sufficient size for learning th...
We acknowledge financial support from the NCCR MARVEL(a National Centre of Competence in Research,funded by the Swiss National Science Foundation,grant No.205602);the Swiss National Science Foundation(SNSF)Project Funding(grant 200021E_206190“FISH4DIET”);The work is also supported by a pilot access grant from the Swiss National Supercomputing Centre(CSCS)on the Swiss share of the LUMI system under project ID“PILOT MC EPFL-NM 01”,a CHRONOS grant from the CSCS on the Swiss share of the LUMI system under project ID“REGULAR MC EPFL-NM 02”,and a grant from the CSCS under project ID s0178.
Maximally-localized Wannier functions(MLWFs)are broadly used to characterize the electronic structure of materials.Generally,one can construct MLWFs describing isolated bands(e.g.valence bands of insulators)or entangl...
The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field.However,a persistent issue remains unsolved during experiments:the interferentia...
Supported by the National Natural Science Foundation of China(61210007).
Learning disentangled representation of data is a key problem in deep learning.Specifically,disentangling 2D facial landmarks into different factors(e.g.,identity and expression)is widely used in the applications of f...
We analyze the spin coincidence experiment considered by Bell in the derivation of Bells theorem. We solve the equation of motion for the spin system with a spin Hamiltonian, Hz, where the magnetic field is only in th...
A straightforward simple proof is given that dark energy is the natural conse-quence of a quantum disentanglement physical process. Thus while the ordinary energy density of the cosmos is equal to half that of Hardy’...