On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement | Paper Citation Record

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Unresolved cited work

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Stuart, and Anima Anandkumar

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Brunton, Joshua L

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement PDE-net: Learning PDEs from data

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement A Robust SINDy Approach by Combining Neural Networks and an Integral Form

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Pde-learn: Using deep learning to discover partial differential equations from noisy, limited data.Neural Networks, 174:106242, 2024

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Unrolled-sindy: A stable explicit method for non linear pde discovery from sparsely sampled data

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement PhysPDE: Rethinking PDE discovery and a physical HYpothesis selection benchmark

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Nathan Kutz, and Steven L

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Discovery of partial differential equations from highly noisy and sparse data with physics-informed information criterion.Research, 6, January 2023

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Mdbench: Bench- marking data-driven methods for model discovery

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Ap- proximation Error of Sobolev Regular Functions with tanh Neural Networks: Theoretical Impact on PINNs

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Error estimates for physics-informed neural networks approximating the navier–stokes equations.IMA Journal of Numerical Analysis, 44(1):83–119, 02 2024

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement On the convergence of PINNs.Bernoulli, 31(3):2127 – 2151, 2025

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Miettinen.Nonlinear multiobjective optimization

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Ro- drigues

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Data-driven discovery of governing differential equations across physical systems

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Lagergren, John T

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Mechanistic PDE networks for dis- covery of governing equations

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Data-driven discovery of PDEs via the adjoint method.Transactions on Machine Learning Research, 2025

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement On the stability of feature selection algorithms.Journal of Machine Learning Research, 18(174):1–54, 2018

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Learning sparse nonlinear dynamics via mixed-integer optimization.Nonlinear Dynamics, 7(11), 2022

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Tanimoto random features for scalable molecular machine learning

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Dynamic bayesian optimization framework for instruction tuning in partial differential equation discovery

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Unresolved cited work

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback

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On the post-hoc Evaluation of PDE Discovery: A Multifaceted Challenge of Scientific Advancement Fasel, J

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