Philippe Wenk

According to our database, Philippe Wenk authored at least 9 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Learning time-continuous dynamics models with Gaussian-process-based gradient matching.

Philippe Wenk

PhD thesis, 2022

Adaptive Gaussian Process Change Point Detection.

Edoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause

Proceedings of the International Conference on Machine Learning, 2022

2021

Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models.

Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

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

Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause

CoRR, 2020

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models.

Diego Agudelo-España, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schölkopf, Stefan Bauer, Manuel Wüthrich

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

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

Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs.

Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer

Proceedings of the 36th International Conference on Machine Learning, 2019

Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs.

Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019