Results 21 to 30 of about 6,454,315 (251)

General implementation of quantum physics-informed neural networks

open access: yesArray, 2023
Recently, a novel type of Neural Network (NNs): the Physics-Informed Neural Networks (PINNs), was discovered to have many applications in computational physics.
Shashank Reddy Vadyala   +1 more
doaj   +1 more source

Bridging Physics and AI: The Power of Physics-Informed Neural Networks (PINNs) in Experimental Studies

open access: yes, 2023
Bridging Physics and AI: The Power of Physics-Informed Neural Networks (PINNs) in Experimental ...
Kamran Mathias
core   +1 more source

Physics-informed neural networks for voltage and SOC estimation

open access: yes, 2022
This work shows benefits of applying simple physics-informed methods to neural networks for battery electrical response ...
Forde, Andrew
core   +1 more source

Physics-informed neural networks for hydraulic transient analysis in pipeline systems

open access: yes, 2022
Physics-informed neural networks for hydraulic transient analysis in pipeline ...
J Ye (8430171)   +3 more
core  

Harnessing the Potential of Physics-Informed Neural Networks (PINNs) in Vortex-Induced Vibration Research

open access: yes, 2023
Harnessing the Potential of Physics-Informed Neural Networks (PINNs) in Vortex-Induced Vibration ...
Lee Mathias
core   +1 more source

Physics Informed Neural Networks for Parametrized Partial Differential Equations

open access: yes, 2023
Physics Informed Neural Networks for Parametrized Partial Differential ...
Prieto Ruiz, Victor Scott
core  

Exploring Vortex-Induced Vibration with Tunable Stiffness and Physics-Informed Neural Networks (PINN)

open access: yes, 2023
Exploring Vortex-Induced Vibration with Tunable Stiffness and Physics-Informed Neural Networks ...
Kevin Lee
core   +1 more source

Physics-informed neural networks for inviscid transonic flows around an airfoil [PDF]

open access: yes
Physics-informed neural networks (PINNs) have gained popularity as a deep-learning-based parametric partial differential equation solver. Especially for engineering applications, this approach is promising because a single neural network (NN) could ...
Wassing, Simon   +2 more
core   +1 more source

Physics informed neural networks for 1D flood routing [PDF]

open access: yes, 2022
Machine learning methods have been widely and successfully applied in hydrological problems. Most of the methods, such as artificial neural networks, have been focused on estimating hydrological data based on observation over time.
Milašinović, Miloš   +7 more
core   +3 more sources

Exercise Capacity, Physical Activity, Fatigue, and Neurocognitive Function in Adult Survivors of Childhood Acute Lymphoblastic Leukemia

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Adult survivors of childhood acute lymphoblastic leukemia (ALL) are at risk of reduced exercise capacity, decreased physical activity levels, persistent fatigue, and neurocognitive deficits. The aim was to investigate exercise capacity and physical activity levels of adult survivors of childhood ALL and their associations with ...
Laura Jess   +5 more
wiley   +1 more source

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