Ko, Jongwoo, and Heeyoung Kim. "Deep Gaussian Process Models for Integrating Multifidelity Experiments with Non-stationary Relationships." IISE Transactions just-accepted (2021): 1-28.
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Jun 11, 2021 - Python
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multifidelity
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PyTorch implementation of Multifidelity Kolmogorov-Arnold Networks (MFKANs) for data-efficient learning. Train accurate models with sparse high-fidelity data by leveraging correlations with abundant low-fidelity data.
machine-learning deep-learning pytorch neural-networks transfer-learning function-approximation kan scientific-machine-learning multifidelity kolmogorov-arnold-networks
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Jan 8, 2026 - Python
🌐 Leverage Multifidelity Kolmogorov-Arnold Networks for efficient training with less high-fidelity data in PyTorch, enhancing model accuracy and performance.
machine-learning deep-learning pytorch neural-networks transfer-learning function-approximation kan github-config scientific-machine-learning multifidelity kolmogorov-arnold-networks
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Jul 7, 2026 - Python
Web app demonstration of multi-fidelity linear regression methods.
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Nov 4, 2024 - Python
Mesh-free NURBS-BEM solver for solenoid magnetic field computation · Multi-fidelity dataset generation for GNN surrogate training
physics-simulation model-reduction nurbs boundary-element-method scientific-machine-learning operator-inference multifidelity surrogate-modeling
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Jun 2, 2026 - Python
Autoregressive Multifidelity Neural Surrogates: Modeling Under Scarce Data Regimes (Research Topic for ACE Group)
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Apr 4, 2026 - Python
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