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10/27/2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
Learning how complex dynamical systems evolve over time is a key challen...
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06/22/2021
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models
Differential equations in general and neural ODEs in particular are an e...
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03/05/2020
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives
Gaussian processes are an important regression tool with excellent analy...
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02/22/2019
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs
Stochastic differential equations are an important modeling class in man...
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02/17/2019
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
Parameter inference in ordinary differential equations is an important p...
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04/12/2018
