Universal Differential Equations for Scientific Machine Learning

13 January 2020

Christopher Rackauckas

Papers citing "Universal Differential Equations for Scientific Machine Learning"

50 / 74 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 33 0 0 17 Apr 2025
Optimal Virtual Model Control for Robotics: Design and Tuning of Passivity-Based Controllers Daniel Larby F. Forni 54 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 72 1 0 15 Dec 2024
When are dynamical systems learned from time series data statistically accurate? Jeongjin Park Nicole Yang Nisha Chandramoorthy AI4TS 34 4 0 09 Nov 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 32 4 0 15 Oct 2024
Structural Constraints for Physics-augmented Learning Simon Kuang Xinfan Lin PINN 26 0 0 07 Oct 2024
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia J. C. V. Gemert Daan Brinks Nergis Tömen 36 0 0 02 Oct 2024
Numerically Robust Fixed-Point Smoothing Without State Augmentation Nicholas Krämer 31 2 0 30 Sep 2024
Differentiable programming across the PDE and Machine Learning barrier N. Bouziani David A. Ham Ado Farsi PINN AI4CE 32 1 0 09 Sep 2024
SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems Patrick Emami Zhaonan Li Saumya Sinha Truc Nguyen 48 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 29 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 30 4 0 04 Aug 2023
Automatic Differentiation for Inverse Problems with Applications in Quantum Transport I. Williams E. Polizzi 11 0 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 13 3 0 31 Mar 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 22 3 0 03 Mar 2023
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 31 3 0 25 Nov 2022
Neural ODEs as Feedback Policies for Nonlinear Optimal Control I. O. Sandoval Panagiotis Petsagkourakis Ehecatl Antonio del Rio Chanona 14 9 0 20 Oct 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery Joon-Hyuk Ko Hankyul Koh Nojun Park W. Jhe 35 8 0 04 Oct 2022
Differentiable Programming for Earth System Modeling Maximilian Gelbrecht Alistair J R White S. Bathiany Niklas Boers 16 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 25 35 0 25 Aug 2022
Interpretable Polynomial Neural Ordinary Differential Equations Colby Fronk Linda R. Petzold 27 26 0 09 Aug 2022
Human Trajectory Prediction via Neural Social Physics Jiangbei Yue Dinesh Manocha He-Nan Wang AI4CE 19 100 0 21 Jul 2022
Automatic differentiation and the optimization of differential equation models in biology S. Frank 14 6 0 10 Jul 2022
j-Wave: An open-source differentiable wave simulator A. Stanziola Simon Arridge B. Cox B. Treeby VLM 33 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 29 0 0 15 Jun 2022
Automated differential equation solver based on the parametric approximation optimization A. Hvatov Tatiana Tikhonova 14 4 0 11 May 2022
Machines of finite depth: towards a formalization of neural networks Pietro Vertechi M. Bergomi PINN 16 2 0 27 Apr 2022
Optimizing differential equations to fit data and predict outcomes S. Frank 19 4 0 16 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 30 124 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
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits Alan Yang J. Xiong Maxim Raginsky E. Rosenbaum AI4TS 16 4 0 14 Feb 2022
Trust in AI: Interpretability is not necessary or sufficient, while black-box interaction is necessary and sufficient Max W. Shen 25 18 0 10 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 22 34 0 08 Feb 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 70 29 0 31 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 24 1,177 0 14 Jan 2022
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic Z. Fei Y. Ryeznik O. Sverdlov C. Tan Weng Kee Wong 21 20 0 25 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data Andrzej Dulny Andreas Hotho Anna Krause AI4CE 22 11 0 15 Nov 2021
Physics-enhanced deep surrogates for partial differential equations R. Pestourie Youssef Mroueh Chris Rackauckas Payel Das Steven G. Johnson PINN AI4CE 25 15 0 10 Nov 2021
A research framework for writing differentiable PDE discretizations in JAX A. Stanziola Simon Arridge B. Cox B. Treeby 21 8 0 09 Nov 2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems Andreas Schlaginhaufen Philippe Wenk Andreas Krause Florian Dorfler 19 15 0 27 Oct 2021