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Shu-Peng Wang

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • q-bio.QM2
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedGMC-PINNs: A new general Monte Carlo PINNs method for solving fractional partial differential equations on irregular domains

1 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

q-bio.QM2024★ 1 cited

Pharmacometrics Modeling via Physics-Informed Neural Networks: Integrating Time-Variant Absorption Rates and Fractional Calculus for Enhancing Prediction Accuracy

Nazanin Ahmadi, Shupeng Wang, George Karniadakis

We present a novel method to improve pharmacokinetics modeling, an essential step of drug development. Conventional models frequently fail to fully represent the intricacies of dru…

q-bio.QM2024

CMINNs: Compartment Model Informed Neural Networks -- Unlocking Drug Dynamics

Nazanin Ahmadi Daryakenari, Shupeng Wang, George Karniadakis

In the field of pharmacokinetics and pharmacodynamics (PKPD) modeling, which plays a pivotal role in the drug development process, traditional models frequently encounter difficult…

cs.LG2024★ 1 cited

GMC-PINNs: A new general Monte Carlo PINNs method for solving fractional partial differential equations on irregular domains

Shupeng Wang, George Em Karniadakis

Physics-Informed Neural Networks (PINNs) have been widely used for solving partial differential equations (PDEs) of different types, including fractional PDEs (fPDES) [29]. Herein,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.