Universal Differential Equations for Scientific Machine Learning

13 January 2020

Christopher Rackauckas

Papers citing "Universal Differential Equations for Scientific Machine Learning"

50 / 91 papers shown

Title
Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming Linus Langenkamp Philip Hannebohm Bernhard Bachmann 36 0 0 06 May 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 81 0 0 25 Apr 2025
Modelling Mean-Field Games with Neural Ordinary Differential Equations Anna C. M. Thöni Yoram Bachrach Tal Kachman 38 0 0 17 Apr 2025
Optimal Virtual Model Control for Robotics: Design and Tuning of Passivity-Based Controllers Daniel Larby F. Forni 62 1 0 20 Jan 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 42 0 0 12 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 77 1 0 15 Dec 2024
When are dynamical systems learned from time series data statistically accurate? Jeongjin Park Nicole Yang Nisha Chandramoorthy AI4TS 36 4 0 09 Nov 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 37 4 0 15 Oct 2024
Structural Constraints for Physics-augmented Learning Simon Kuang Xinfan Lin PINN 28 0 0 07 Oct 2024
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia Jan van Gemert Daan Brinks Nergis Tömen 38 0 0 02 Oct 2024
Numerically Robust Fixed-Point Smoothing Without State Augmentation Nicholas Krämer 39 2 0 30 Sep 2024
Differentiable programming across the PDE and Machine Learning barrier N. Bouziani David A. Ham Ado Farsi PINN AI4CE 37 1 0 09 Sep 2024
SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems Patrick Emami Zhaonan Li Saumya Sinha Truc Nguyen 56 1 0 30 May 2024
Interventionally Consistent Surrogates for Agent-based Simulators Joel Dyer Nicholas Bishop Yorgos Felekis Fabio Massimo Zennaro Anisoara Calinescu Theodoros Damoulas Michael Wooldridge 19 6 0 18 Dec 2023
Enhancing Low-Order Discontinuous Galerkin Methods with Neural Ordinary Differential Equations for Compressible Navier--Stokes Equations Shinhoo Kang Emil M. Constantinescu AI4CE 22 0 0 29 Oct 2023
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 34 1 0 06 Sep 2023
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 23 3 0 21 Aug 2023
Branched Latent Neural Maps M. Salvador Alison Lesley Marsden 38 4 0 04 Aug 2023
Automatic Differentiation for Inverse Problems with Applications in Quantum Transport I. Williams E. Polizzi 18 1 0 18 Jul 2023
Trainability, Expressivity and Interpretability in Gated Neural ODEs T. Kim T. Can K. Krishnamurthy AI4CE 35 4 0 12 Jul 2023
Neural Astrophysical Wind Models Dustin D. Nguyen 16 2 0 20 Jun 2023
An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential Equations Mattia Silvestri Federico Baldo Eleonora Misino M. Lombardi AI4CE 16 1 0 17 Jun 2023
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators Haakon Noren Sølve Eidnes E. Celledoni 21 3 0 06 Jun 2023
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas Mohamed Tarek J. Storópoli Casey B. Davis C. Elrod Julius Krumbiegel Chris Rackauckas V. Ivaturi GP 23 3 0 31 Mar 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 24 3 0 03 Mar 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences Chaopeng Shen A. Appling Pierre Gentine Toshiyuki Bandai H. Gupta ... Chris Rackauckas Tirthankar Roy Chonggang Xu Binayak Mohanty K. Lawson AI4CE 42 14 0 10 Jan 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control Adam J. Thorpe Cyrus Neary Franck Djeumou Meeko Oishi Ufuk Topcu 35 7 0 09 Jan 2023
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks Cyrus Neary Ufuk Topcu PINN AI4CE 20 12 0 01 Dec 2022
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 39 3 0 25 Nov 2022
The Past Does Matter: Correlation of Subsequent States in Trajectory Predictions of Gaussian Process Models Steffen Ridderbusch Sina Ober-Blobaum Paul Goulart 24 2 0 20 Nov 2022
Neural ODEs as Feedback Policies for Nonlinear Optimal Control I. O. Sandoval Panagiotis Petsagkourakis Ehecatl Antonio del Rio Chanona 25 9 0 20 Oct 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery Joon-Hyuk Ko Hankyul Koh Nojun Park W. Jhe 46 8 0 04 Oct 2022
A Robust Learning Methodology for Uncertainty-aware Scientific Machine Learning models Erbet Costa Almeida C. Rebello M. Fontana L. Schnitman Idelfonso B. R. Nogueira 19 9 0 05 Sep 2022
Differentiable Programming for Earth System Modeling Maximilian Gelbrecht Alistair J R White S. Bathiany Niklas Boers 21 16 0 29 Aug 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 32 36 0 25 Aug 2022
Interpretable Polynomial Neural Ordinary Differential Equations Colby Fronk Linda R. Petzold 27 27 0 09 Aug 2022
Physics-informed Machine Learning of Parameterized Fundamental Diagrams J.R.L. Koch Thomas Maxner Vinay C. Amatya A. Ranjbari Chase P. Dowling AI4CE PINN 11 2 0 01 Aug 2022
Human Trajectory Prediction via Neural Social Physics Jiangbei Yue Tianyi Zhou He Wang AI4CE 26 101 0 21 Jul 2022
Structural Inference of Networked Dynamical Systems with Universal Differential Equations James Koch Zhao Chen Aaron Tuor Ján Drgoňa D. Vrabie PINN 28 10 0 11 Jul 2022
Automatic differentiation and the optimization of differential equation models in biology S. Frank 22 6 0 10 Jul 2022
j-Wave: An open-source differentiable wave simulator A. Stanziola Simon Arridge B. Cox B. Treeby VLM 41 21 0 30 Jun 2022
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations Jongwan Kim Dongjin Lee Byunggook Na Seongsik Park Jeonghee Jo Sung-Hoon Yoon 31 0 0 15 Jun 2022
Automated differential equation solver based on the parametric approximation optimization A. Hvatov Tatiana Tikhonova 16 4 0 11 May 2022
Machines of finite depth: towards a formalization of neural networks Pietro Vertechi M. Bergomi PINN 21 2 0 27 Apr 2022
Optimizing differential equations to fit data and predict outcomes S. Frank 33 4 0 16 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 45 127 0 11 Apr 2022
Monarch: Expressive Structured Matrices for Efficient and Accurate Training Tri Dao Beidi Chen N. Sohoni Arjun D Desai Michael Poli Jessica Grogan Alexander Liu Aniruddh Rao Atri Rudra Christopher Ré 22 87 0 01 Apr 2022
Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy D. Feng Jiangtao Liu K. Lawson Chaopeng Shen BDL AI4CE 18 117 0 28 Mar 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 25 22 0 28 Feb 2022
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits Alan Yang J. Xiong Maxim Raginsky E. Rosenbaum AI4TS 24 4 0 14 Feb 2022