Neural ODEs (NODEs) [Physics Informed Machine Learning] @Eigensteve
Neural ODEs (NODEs) [Physics Informed Machine Learning]  @Eigensteve
Uploaded June 2024 | Updated September 2026, 2 weeks ago
This video describes Neural ODEs, a powerful machine learning approach to learn ODEs from data.

This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

%%% CHAPTERS %%%
00:00 Intro
02:09 Background: ResNet
05:05 From ResNet to ODE
07:59 ODE Essential Insight/ Why ODE outperforms ResNet
// 09:05 ODE Essential Insight Rephrase 1
// 09:54 ODE Essential Insight Rephrase 2
11:11 ODE Performance vs ResNet Performance
12:52 ODE extension: HNNs
14:03 ODE extension: LNNs
14:45 ODE algorithm overview/ ODEs and Adjoint Calculation
22:24 Outro
Neural ODEs (NODEs) [Physics Informed Machine Learning]Proof of the Central Limit TheoremNew Book!!!  Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and ControlMarkovs Inequality in Probability: First Order EstimatesChebyshevs Inequality in Probability: Second Order EstimatesThe Future of Model Based Engineering: Collimator 2.0Complex Analysis L06: Analytic Functions and Cauchy-Riemann ConditionsNonlinear parametric models of viscoelastic fluid flows with SINDyRescaling the Normal Distribution to Mean Zero and Variance OneJoint Probability Distributions: Marginal and Conditional DensitiesLinear Systems of Differential Equations with Forcing: Convolution and the Dirac Delta FunctionConjugate Priors Example: Normal Distribution and the Exponential Family of Distributions
Steve Brunton |

Neural ODEs (NODEs) [Physics Informed Machine Learning]

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