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Guang Lin

Coefficient-to-Basis Network: A Fine-Tunable Operator Learning Framework for Inverse Problems with Adaptive Discretizations and Theoretical Guarantees

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Mar 11, 2025
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Active operator learning with predictive uncertainty quantification for partial differential equations

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Mar 05, 2025
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LAPD: Langevin-Assisted Bayesian Active Learning for Physical Discovery

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Mar 04, 2025
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Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation

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Feb 25, 2025
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Exploring Non-Convex Discrete Energy Landscapes: A Langevin-Like Sampler with Replica Exchange

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Jan 28, 2025
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LLM Reasoning Engine: Specialized Training for Enhanced Mathematical Reasoning

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Dec 28, 2024
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Adversarial Autoencoders in Operator Learning

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Dec 10, 2024
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Some Best Practices in Operator Learning

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Dec 09, 2024
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Loss Terms and Operator Forms of Koopman Autoencoders

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Dec 05, 2024
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DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning

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Nov 11, 2024
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