Article

Universal Differential Equations for Scientific Machine Learning

2020-08-31

Abstract excerpt

<title>Abstract</title> <p>In the context of science, the well-known adage “a picture is worth a thousand words” might well be “a model is worth a thousand datasets.” Scientific models, such as Newtonian physics or biological gene regulatory networks, are human-driven simplifications of complex phenomena that serve as surrogates for the countless experiments that validated the models. Recently, machine learning h...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 755d405a-81e8-5011-9a4a-0f252472fb92
DOI: 10.21203/rs.3.rs-55125/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Universal Differential Equations for Scientific Machine LearningDOI 10.21203/rs.3.rs-55125/v1Read

Physiology-informed regularization enables training of universal differential equation systems for biological applicationsSemantic proximity Read

Dynamic Models of Neural Population DynamicsSemantic proximity Read

Unsupervised physics-informed neural network in reaction-diffusion biology models (Ulcerative colitis and Crohn’s disease cases) A preliminary studySemantic proximity Read

Integrating Kolmogorov-Arnold Networks with Ordinary Differential Equations for Efficient, Interpretable and Robust Deep Learning: A Case Study in the Epidemiology of Infectious DiseasesSemantic proximity Read

Biologically informed NeuralODEs for genome-wide regulatory dynamicsSemantic proximity Read

Predicting COVID-19 pandemic waves with biologically and behaviorally informed universal differential equationsSemantic proximity Read

Mathematical Modeling Of Systems BiologySemantic proximity Read

Information theory for data-driven model reduction in physics and biologySemantic proximity Read

Identification of Gene Regulation Models from Single-Cell DataSemantic proximity Read

Benchmark Problems for Dynamic Modeling of Intracellular ProcessesSemantic proximity Read

Unraveling Hidden Interactions in Complex Systems with Deep LearningSemantic proximity Read

Using constraints and their value for optimization of large ODE systems.Semantic proximity Read