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Daniel M. Tartakovsky

Stanford University

Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling

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Oct 16, 2024
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Baseflow identification via explainable AI with Kolmogorov-Arnold networks

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Oct 10, 2024
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High-Precision Geosteering via Reinforcement Learning and Particle Filters

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Feb 09, 2024
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Neural oscillators for magnetic hysteresis modeling

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Aug 23, 2023
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Neural oscillators for generalization of physics-informed machine learning

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Aug 17, 2023
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Learning Nonautonomous Systems via Dynamic Mode Decomposition

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Jun 27, 2023
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Discovering Sparse Hysteresis Models: A Data-driven Study for Piezoelectric Materials and Perspectives on Magnetic Hysteresis

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Feb 16, 2023
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Machine Learning in Heterogeneous Porous Materials

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Feb 04, 2022
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Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

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Oct 24, 2021
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Transfer Learning on Multi-Fidelity Data

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Apr 29, 2021
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