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Found 9 papers, 5 papers with code
Theoretical formulations on thermodynamics of quantum impurity systems
In this work, we put forward the theoretical foundation toward thermodynamics of quantum impurity systems measurable in experiments.
Quantum Physics Statistical Mechanics
Marcus' electron transfer rate revisited via a Rice-Ramsperger-Kassel-Marcus analogue: A unified formalism for linear and nonlinear solvation scenarios
In this work, on the basis of the thermodynamic solvation potentials analysis, we reexamine Marcus' formula with respect to the Rice-Ramsperger-Kassel-Marcus (RRKM) theory.
Chemical Physics
Consensus Graph Learning for Multi-view Clustering
Furthermore, we unify the spectral embedding and low rank tensor learning into a unified optimization framework to determine the spectral embedding matrices and tensor representation jointly.
Tensor-Based Multi-View Block-Diagonal Structure Diffusion for Clustering Incomplete Multi-View Data
In this paper, we propose a novel incomplete multi-view clustering method, in which a tensor nuclear norm regularizer elegantly diffuses the information of multi-view block-diagonal structure across different views.
Multi-layered Semantic Representation Network for Multi-label Image Classification
To this end, this paper designs a Multi-layered Semantic Representation Network (MSRN) which discovers both local and global semantics of labels through modeling label correlations and utilizes the label semantics to guide the semantic representations learning at multiple layers through an attention mechanism.
Ranked #6 on
Multi-Label Classification
on PASCAL VOC 2007
High-order Correlation Preserved Incomplete Multi-view Subspace Clustering
Specifically, multiple affinity matrices constructed from the incomplete multi-view data are treated as a thirdorder low rank tensor with a tensor factorization regularization which preserves the high-order view correlation and sample correlation.
Twin Graph-based Anomaly Detection via Attentive Multi-Modal Learning for Microservice System
The MST graph provides a virtual representation of the status and scheduling relationships among service instances of a real-world microservice system.
Point Cloud Pre-training with Diffusion Models
This generator aggregates the features extracted by the backbone and employs them as the condition to guide the point-to-point recovery from the noisy point cloud, thereby assisting the backbone in capturing both local and global geometric priors as well as the global point density distribution of the object.
Neural Network Approach for Non-Markovian Dissipative Dynamics of Many-Body Open Quantum Systems
Simulating the dynamics of open quantum systems coupled to non-Markovian environments remains an outstanding challenge due to exponentially scaling computational costs.
