Learning unknown ODE models with Gaussian processes

12 March 2018

Harri Lähdesmäki

Papers citing "Learning unknown ODE models with Gaussian processes"

20 / 20 papers shown

Title
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck Arno Solin Theodoros Damoulas 31 0 0 20 Sep 2024
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 41 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 46 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
Learning ODE Models with Qualitative Structure Using Gaussian Processes Steffen Ridderbusch Christian Offen Sina Ober-Blobaum Paul Goulart 6 15 0 10 Nov 2020
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
Black-Box Inference for Non-Linear Latent Force Models W. Ward Tom Ryder D. Prangle Mauricio A. Alvarez DRL 18 14 0 21 Jun 2019
ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL DRL 21 88 0 27 May 2019