Search Results for author: Philippe Wenk

Found 6 papers, 6 papers with code

Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems

1 code implementation NeurIPS 2021 Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler

To this end, neural ODEs regularized with neural Lyapunov functions are a promising approach when states are fully observed.

SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives

1 code implementation5 Mar 2020 Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause

Gaussian processes are an important regression tool with excellent analytic properties which allow for direct integration of derivative observations.

Gaussian Processes

ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems

2 code implementations17 Feb 2019 Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer

Parameter inference in ordinary differential equations is an important problem in many applied sciences and in engineering, especially in a data-scarce setting.

Gaussian Processes Model Selection

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