neural-numerical-methods

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jseongnam / taylor-root-prediction

Official IEEE Access implementation for Taylor coefficient-based neural root prediction with Transformer interval localization and residual validation.

root-finding pytorch transformer numerical-analysis taylor-series scientific-machine-learning residual-validation neural-numerical-methods

Updated May 29, 2026
Jupyter Notebook

jseongnam / single-variable-root-prediction

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Neural root prediction pipeline for single-variable synthetic equations with branch-aware learning and residual validation.

flask machine-learning root-finding pytorch numerical-analysis taylor-series scientific-machine-learning residual-validation neural-numerical-methods single-variable-equations

Updated May 30, 2026
Python

jseongnam / cai-Colebrook

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Hybrid neural-numerical warm-start correction framework for Colebrook-White pipe-flow equations with Newton refinement.

pytorch numerical-analysis newton-method colebrook-white scientific-machine-learning warm-start pipe-flow hydraulic-systems neural-numerical-methods neural-correction baseline-aware-learning taylor-coefficients

Updated May 30, 2026
Python

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