Fusionformer: A Novel Adversarial Transformer Utilizing Fusion Attention for Multivariate Anomaly Detection [0.03%]
融合变压器：一种利用融合注意力机制进行多变量异常检测的新对抗转换器
Chuang Wang,Zidong Wang,Hongli Dong et al.
Chuang Wang et al.
Multivariate time series forecasting (MTSF) is of significant importance in the enhancement and optimization of real-world applications. The task of MTSF poses substantial challenges due to the unpredictability of temporal patterns and the ...
Topology Identification of Weighted Complex Networks Under Intermittent Control and Its Application in Neural Networks [0.03%]
间歇控制下带权复杂网络拓扑结构辨识及其在神经网络中的应用
Huiling Chen,Chunmei Zhang,Han Yang
Huiling Chen
Topology identification of stochastic complex networks is an important topic in network science. In modern identification techniques under a continuous framework, the controller has a negative dynamic gain (feedback gain), such that stochas...
Learning Spatial-Temporal Regularized Tensor Sparse RPCA for Background Subtraction [0.03%]
用于背景减除的基于时空正则张量稀疏RPCA学习方法研究
Basit Alawode,Sajid Javed
Basit Alawode
Background subtraction in videos is a core challenge in computer vision, aiming to accurately identify moving objects. Robust principal component analysis (RPCA) has emerged as a promising unsupervised (US) paradigm for this task, showing s...
Dan Zhang,Tong Zhang,C L Philip Chen et al.
Dan Zhang et al.
Broad learning system (BLS) have demonstrated excellent performance in terms of both speed and accuracy in tasks such as image classification. In BLS, the feature nodes predominantly utilize linear features, and sparse representation is mai...
Shuyi Ji,Yifan Feng,Donglin Di et al.
Shuyi Ji et al.
The hypergraph neural network (HGNN) is an emerging powerful tool for modeling and learning complex, high-order correlations among entities upon hypergraph structures. While existing HGNN-based approaches excel in modeling high-order correl...
Physics-Driven Anomaly Detection and Correction for Spectroscopic Parameter Estimation [0.03%]
物理驱动的光谱参数估计算法的异常检测与修正
Ruiyuan Kang,Panos Liatsis
Ruiyuan Kang
Machine learning (ML) techniques are popular in many parameter estimation tasks; however, they face challenges in the real-world deployment due to the lack of robustness to errors. ML estimators are not able to ascertain performance in the ...
Semantics-Aware Hierarchical Decision Framework for Embodied Visual Room Rearrangement [0.03%]
考虑语义的分层决策框架在具象视觉房间重组中的应用
Xinzhu Liu,Di Guo,Huaping Liu
Xinzhu Liu
In embodied visual room rearrangement, the agent needs to recover the scene state to the goal state through interacting with the environment based on the egocentric visual observations after the locations and states of some objects are chan...
Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery [0.03%]
元-MolNet：用于少量样例药物发现的跨领域基准测试
Qiujie Lv,Guanxing Chen,Ziduo Yang et al.
Qiujie Lv et al.
Predicting the pharmacological activity, toxicity, and pharmacokinetic properties of molecules is a central task in drug discovery. Existing machine learning methods are transferred from one resource rich molecular property to another data ...
Dynamic Neural Network Structure: A Review for its Theories and Applications [0.03%]
动态神经网络结构：对其理论与应用的回顾
Jifeng Guo,C L Philip Chen,Zhulin Liu et al.
Jifeng Guo et al.
The dynamic neural network (DNN), in contrast to the static counterpart, offers numerous advantages, such as improved accuracy, efficiency, and interpretability. These benefits stem from the network's flexible structures and parameters, mak...
Self-Triggered Approximate Optimal Neuro-Control for Nonlinear Systems Through Adaptive Dynamic Programming [0.03%]
通过自适应动态规划实现非线性系统的自我触发近似最优神经网络控制
Bo Zhao,Shunchao Zhang,Derong Liu
Bo Zhao
In this article, a novel self-triggered approximate optimal neuro-control scheme is presented for nonlinear systems by utilizing adaptive dynamic programming (ADP). According to the Bellman principle of optimality, the cost function of the ...