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Showing 1–5 of 5 results
Advanced filters: Author: Aditya Tandon Clear advanced filters
  • Speech brain-computer interfaces face challenges scaling across individuals with different brain organization. Using minimally invasive recordings from 25 patients, the authors developed transfer learning methods that enable robust speech decoding even with incomplete brain coverage.

    • Aditya Singh
    • Tessy Thomas
    • Nitin Tandon
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-12
  • Network embedding is a machine learning technique for construction of low-dimensional representations of large networks. Gu et al. propose a method for the identification of an optimal embedding dimension for the encoding of network structural information inspired by natural language processing.

    • Weiwei Gu
    • Aditya Tandon
    • Filippo Radicchi
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-10
  • Physics-aware deep generative models are used to design material microstructures exhibiting tailored properties. Multi-fidelity data are used to create inexpensive yet accurate machine learning surrogates for evaluating the physics-based constraints within such design frameworks.

    • Xian Yeow Lee
    • Joshua R. Waite
    • Soumik Sarkar
    Research
    Nature Computational Science
    Volume: 1, P: 229-238
  • Ali Rabeh, Ethan Herron and colleagues benchmark diverse scientific machine learning models, including neural operators and vision transformer-based foundation models, for fluid flow prediction over intricate geometries using a unified scoring framework. They show that geometry representations can have a measurable impact on the accuracy and generalization of different models.

    • Ali Rabeh
    • Ethan Herron
    • Baskar Ganapathysubramanian
    ResearchOpen Access
    Communications Engineering
    Volume: 4, P: 1-11