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Tag: reduction

  • Structural Dimension Reduction in Bayesian Networks

    Structural Dimension Reduction in Bayesian Networks arXiv:2601.08236v1 Announce Type: new Abstract: This work introduces a novel technique, named structural dimension reduction, to collapse a Bayesian network onto a minimum and localized one while ensuring that probabilistic inferences between the original and reduced networks remain consistent. To this end, we propose a new combinatorial structure in…

  • Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics

    Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics arXiv:2512.11090v1 Announce Type: new Abstract: Many problems in science and engineering involve time-dependent, high dimensional datasets arising from complex physical processes, which are costly to simulate. In this work, we propose WeldNet: Windowed Encoders for Learning Dynamics, a data-driven nonlinear model reduction framework to build…

  • Supervised Quadratic Feature Analysis: An Information Geometry Approach to Dimensionality Reduction

    Supervised Quadratic Feature Analysis: An Information Geometry Approach to Dimensionality Reduction arXiv:2502.00168v1 Announce Type: new Abstract: Supervised dimensionality reduction aims to map labeled data to a low-dimensional feature space while maximizing class discriminability. Despite the availability of methods for learning complex non-linear features (e.g. Deep Learning), there is an enduring demand for dimensionality reduction methods…

  • A dimensionality reduction technique based on the Gromov-Wasserstein distance

    A dimensionality reduction technique based on the Gromov-Wasserstein distance arXiv:2501.13732v1 Announce Type: new Abstract: Analyzing relationships between objects is a pivotal problem within data science. In this context, Dimensionality reduction (DR) techniques are employed to generate smaller and more manageable data representations. This paper proposes a new method for dimensionality reduction, based on optimal transportation…

  • Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction

    Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction arXiv:2412.08961v1 Announce Type: new Abstract: We introduce a unified, flexible, and easy-to-implement framework of sufficient dimension reduction that can accommodate both linear and nonlinear dimension reduction, and both the conditional distribution and the conditional mean as the targets of estimation. This unified framework…