يعرض 1 - 9 نتائج من 9 نتيجة بحث عن '"Basir, Shamsulhaq"', وقت الاستعلام: 0.35s تنقيح النتائج
  1. 1
    Report
    Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural Networks

    المؤلفون: Hu, Qifeng, Basir, Shamsulhaq, Senocak, Inanc

    مصطلحات موضوعية: Computer Science - Machine Learning

    URL الوصول: http://arxiv.org/abs/2409.13644

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  2. 2
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    A Generalized Schwarz-type Non-overlapping Domain Decomposition Method using Physics-constrained Neural Networks

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing, Mathematics - Numerical Analysis, Physics - Fluid Dynamics

    URL الوصول: http://arxiv.org/abs/2307.12435

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  3. 3
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    An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    مصطلحات موضوعية: Computer Science - Machine Learning, Physics - Computational Physics, Physics - Fluid Dynamics, 35Qxx, 35Exx, 76Dxx, 68Wxx, 65Mxx, 65Kxx, 49Mxx, 49Kxx, G.1.6, G.1.8, G.1.10, J.2, I.2, I.6

    URL الوصول: http://arxiv.org/abs/2306.04904

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  4. 4
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    Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)

    المؤلفون: Basir, Shamsulhaq

    المصدر: Commun. Comput. Phys., 33 (2023), pp. 1240-1269

    مصطلحات موضوعية: Computer Science - Machine Learning, Mathematics - Numerical Analysis, Physics - Computational Physics, Physics - Fluid Dynamics

    URL الوصول: http://arxiv.org/abs/2209.09988

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  5. 5
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    Critical Investigation of Failure Modes in Physics-informed Neural Networks

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    مصطلحات موضوعية: Computer Science - Machine Learning, Mathematics - Numerical Analysis

    URL الوصول: http://arxiv.org/abs/2206.09961

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  6. 6
    Report
    Characterizing and Mitigating the Difficulty in Training Physics-informed Artificial Neural Networks under Pointwise Constraints

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    مصطلحات موضوعية: Computer Science - Machine Learning, Physics - Fluid Dynamics

    URL الوصول: http://arxiv.org/abs/2206.09321

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  7. 7
    Report
    Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    المصدر: Journal of Computational Physics, Volume 463, 15 August 2022, 111301

    مصطلحات موضوعية: Physics - Computational Physics, Computer Science - Machine Learning, Mathematics - Numerical Analysis, Physics - Fluid Dynamics

    URL الوصول: http://arxiv.org/abs/2109.14860

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  8. 8
    Electronic Resource
    Scientific Machine Learning for Transport Phenomena in Thermal and Fluid Sciences

    المؤلفون: Basir, Shamsulhaq

    مصطلحات الفهرس: University of Pittsburgh ETD, PeerReviewed

    URL: http://d-scholarship.pitt.edu/44401/1/Shams_PhD_Thesis_PreApproval.pdf
    http://worldcat.org/search?q=on:PIT+http://d-scholarship.pitt.edu/cgi/oai2+DCG_ENTIRE_REPOSITORY+CNTCOLL
    http://d-scholarship.pitt.edu/44401/
    http://d-scholarship.pitt.edu/44401

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  9. 9
    Academic Journal
    Physics and equality constrained artificial neural networks: Application to forward and inverse problems with multi-fidelity data fusion

    المؤلفون: Basir, Shamsulhaq, Senocak, Inanc

    وصف الملف: application/pdf; text/plain

    Relation: http://d-scholarship.pitt.edu/43060/1/2109.14860v4.pdf; http://d-scholarship.pitt.edu/43060/6/licenseagreement_dscholarship.txt; Basir, Shamsulhaq and Senocak, Inanc (2022) Physics and equality constrained artificial neural networks: Application to forward and inverse problems with multi-fidelity data fusion. JOURNAL OF COMPUTATIONAL PHYSICS, 463. ISSN 0021-9991

    الاتاحة: http://d-scholarship.pitt.edu/43060/
    http://d-scholarship.pitt.edu/43060/1/2109.14860v4.pdf
    http://d-scholarship.pitt.edu/43060/6/licenseagreement_dscholarship.txt

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