Mutual-Energy Inner Product Optimization Method for Constructing Feature Coordinates and Image Classification in Machine Learning by Yuanxiu Wang

“…This paper proposes the mutual-energy inner product optimization method for constructing a feature coordinate system. …”
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A Koopman Reachability Approach for Uncertainty Analysis in Ground Vehicle Systems by Alok Kumar, Bhagyashree Umathe, Atul Kelkar

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Spatially explicit predictions using spatial eigenvector maps by Guillaume Guénard, Pierre Legendre

“…It unites features of a method called “Moran's eigenvector maps” (MEM) and those of spatial interpolation, and produces sets of descriptors that can be used with any other modelling method, such as regressions, support vector machines, regression trees, artificial neural networks and so on. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…In this paper, we propose the OnLine Variational Gaussian Process (OLVGP) algorithm, which introduces a novel approach for dynamically managing the number of inducing points based on the concept of eigenfunction inducing features. Unlike traditional methods that rely on a fixed number of inducing points, OLVGP adaptively adjusts the number of inducing points as new data arrives and optimizes them from the model, ensuring that the model remains computationally efficient while maintaining high predictive accuracy. …”
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Learning neural operators on Riemannian manifolds by Chen Gengxiang, Liu Xu, Meng Qinglu, Chen Lu, Liu Changqing, Li Yingguang

“…Learning mappings between functions (operators) defined on complex computational domains is a common theoretical challenge in machine learning. Existing operator learning methods mainly focus on regular computational domains, and have many components that rely on Euclidean structural data. …”
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