AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
Bernhard Schölkopf , Michael A. Osborne , Andreas Krause , Stefan Bauer
international conference on machine learning 97 1 -10
14
2019
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs
Joachim M. Buhmann , Alkis Gotovos , Andreas Krause , Stefan Bauer
international conference on artificial intelligence and statistics 1351 -1360
7
2019
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models
Diego Agudelo-Espana , Andrii Zadaianchuk , Philippe Wenk , Aditya Garg
2020 IEEE International Conference on Robotics and Automation (ICRA) 8151 -8157
5
2020
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
Philippe Wenk , Gabriele Abbati , Michael A. Osborne , Bernhard Schölkopf
national conference on artificial intelligence 34 ( 04) 6364 -6371
6
2020
Learning stable deep dynamics models for partially observed or delayed dynamical systems
Andreas Schlaginhaufen , Philippe Wenk , Andreas Krause , Florian Dorfler
Advances in Neural Information Processing Systems 34 11870 -11882
6
2021
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models
Lenart Treven , Philippe Wenk , Florian Dorfler , Andreas Krause
Advances in Neural Information Processing Systems 34 29780 -29793
1
2021
Sleipnir: Deterministic and provably accurate feature expansion for gaussian process regression with derivatives
Emmanouil Angelis , Philippe Wenk , Bernhard Schölkopf , Stefan Bauer
arXiv preprint arXiv:2003.02658
6
2020
Adaptive gaussian process change point detection
Edoardo Caldarelli , Philippe Wenk , Stefan Bauer , Andreas Krause
International Conference on Machine Learning 2542 -2571
9
2022
Learning time-continuous dynamics models with Gaussian-process-based gradient matching
Philippe Wenk
ETH Zürich Zürich
2022
Stabilizing Flight
Samuel Gyger , Andreas Steger , Philippe Wenk
2013
Deep Dynamics Learning For Thermoacoustics
Philippe Wenk