{
"OpenAlex": {
"display_name": "Physics-Informed Neural Networks for Scientific Computing",
"description": "This cluster of papers focuses on the development and application of physics-informed neural networks for scientific computing, particularly in the context of solving partial differential equations, model reduction, fluid dynamics, dynamic mode decomposition, and nonlinear systems. The research explores the integration of deep learning techniques with traditional numerical methods to address complex problems in physics-based modeling and simulation.",
"keywords": [
"Deep Learning",
"Partial Differential Equations",
"Model Reduction",
"Fluid Dynamics",
"Dynamic Mode Decomposition",
"Nonlinear Systems",
"Machine Learning",
"Data-Driven Modeling",
"Numerical Computing",
"Inverse Problems"
],
"ids": {
"openalex": "https://openalex.org/T11206",
"wikipedia": "https://en.wikipedia.org/wiki/Physics-informed_neural_networks"
},
"subfield": {
"id": "https://openalex.org/subfields/3109",
"display_name": "Statistical and Nonlinear Physics"
},
"field": {
"id": "https://openalex.org/fields/31",
"display_name": "Physics and Astronomy"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
},
"updated_date": "2024-08-12T06:00:29.116726",
"created_date": "2024-01-23",
"type": "topic",
"oa_id": "T11206",
"id": "https://openalex.org/T11206"
}
}