Learning unknown ODE models with Gaussian processes

Learning unknown ODE models with Gaussian processes

12 March 2018

Markus Heinonen

Çağatay Yıldız

Henrik Mannerstrom

Jukka Intosalmi

Harri Lähdesmäki

Papers citing "Learning unknown ODE models with Gaussian processes"

16 / 16 papers shown

Title
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching Nan Jiang Md Nasim Yexiang Xue 42 0 0 02 Sep 2024
Machine Learning for Predicting Chaotic Systems Christof Schötz Alistair J R White Maximilian Gelbrecht Niklas Boers AI4CE 36 4 0 29 Jul 2024
Exact Inference for Continuous-Time Gaussian Process Dynamics K. Ensinger Nicholas Tagliapietra Sebastian Ziesche Sebastian Trimpe 29 1 0 05 Sep 2023
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers Kai Lagemann C. Lagemann Swarnava Mukherjee 44 2 0 21 Jun 2023
On the Identifiablility of Nonlocal Interaction Kernels in First-Order Systems of Interacting Particles on Riemannian Manifolds Sui Tang Malik Tuerkoen Hanming Zhou 35 4 0 21 May 2023
Free-Form Variational Inference for Gaussian Process State-Space Models Xuhui Fan Edwin V. Bonilla T. O’Kane Scott A. Sisson 16 9 0 20 Feb 2023
Learning nonparametric ordinary differential equations from noisy data Kamel Lahouel Michael L. Wells Victor Rielly Ethan Lew David M Lovitz Bruno Jedynak 31 5 0 30 Jun 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes D. Long Zihan Wang Aditi S. Krishnapriyan Robert M. Kirby Shandian Zhe Michael W. Mahoney AI4CE 34 14 0 24 Feb 2022
Approximate Latent Force Model Inference Jacob Moss Felix L. Opolka Bianca Dumitrascu Pietro Lio 49 3 0 24 Sep 2021
Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO Xuan Wu Jizong Han Dian Wang Pengyue Gao Quanlong Cui ... Han Huang Heow Pueh Lee Chunyan Miao You Zhou Chunguo Wu 16 34 0 25 Aug 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processes Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 30 16 0 21 Jun 2021
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 26 5 0 04 Jun 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 24 44 0 06 May 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 28 20 0 04 Mar 2021
Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: A New Insight into Machine Learning Applications Yun Yuan X. Yang Zhao Zhang Shandian Zhe AI4CE 34 95 0 06 Feb 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen David Duvenaud 17 310 0 05 Jan 2020