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2001.04385
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Universal Differential Equations for Scientific Machine Learning

v1v2v3v4 (latest)

Universal Differential Equations for Scientific Machine Learning

13 January 2020

Christopher Rackauckas

Julius Martensen

Dominic J. Skinner

ArXiv (abs)PDF HTML

Papers citing "Universal Differential Equations for Scientific Machine Learning"

50 / 278 papers shown

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

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Hard-Constrained Neural Networks with Physics-Embedded Architecture for Residual Dynamics Learning and Invariant Enforcement in Cyber-Physical Systems

Hard-Constrained Neural Networks with Physics-Embedded Architecture for Residual Dynamics Learning and Invariant Enforcement in Cyber-Physical Systems

Enzo Nicolás Spotorno

Josafat Leal Filho

Antônio Augusto Fröhlich

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28 Nov 2025

Adaptive tumor growth forecasting via neural & universal ODEs

Adaptive tumor growth forecasting via neural & universal ODEs

Kavya Subramanian

Prathamesh Dinesh Joshi

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27 Nov 2025

CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection

CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection

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23 Nov 2025

CODE: A global approach to ODE dynamics learning

CODE: A global approach to ODE dynamics learning

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19 Nov 2025

PCARNN-DCBF: Minimal-Intervention Geofence Enforcement for Ground Vehicles

PCARNN-DCBF: Minimal-Intervention Geofence Enforcement for Ground Vehicles

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19 Nov 2025

Method of Manufactured Learning for Solver-free Training of Neural Operators

Method of Manufactured Learning for Solver-free Training of Neural Operators

256

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17 Nov 2025

Physics-Informed Neural ODEs with Scale-Aware Residuals for Learning Stiff Biophysical Dynamics

Physics-Informed Neural ODEs with Scale-Aware Residuals for Learning Stiff Biophysical Dynamics

Kamalpreet Singh Kainth

Prathamesh Dinesh Joshi

Raj Abhijit Dandekar

186

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13 Nov 2025

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series

393

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10 Nov 2025

Experimental differentiation and extremization with analog quantum circuits

Experimental differentiation and extremization with analog quantum circuits

V. Abramavičius

...

Louis-Paul Henry

Antonio A. Gentile

Savvas Varsamopoulos

140

1

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23 Oct 2025

EARS-UDE: Evaluating Auditory Response in Sensory Overload with Universal Differential Equations

EARS-UDE: Evaluating Auditory Response in Sensory Overload with Universal Differential Equations

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115

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16 Oct 2025

Machine Learning Workflows in Climate Modeling: Design Patterns and Insights from Case Studies

Machine Learning Workflows in Climate Modeling: Design Patterns and Insights from Case Studies

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226

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30 Sep 2025

A study of Universal ODE approaches to predicting soil organic carbon

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167

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29 Sep 2025

Learning From Simulators: A Theory of Simulation-Grounded Learning

Learning From Simulators: A Theory of Simulation-Grounded Learning

Marisa Eisenberg

231

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Unified Spatiotemporal Physics-Informed Learning (USPIL): A Framework for Modeling Complex Predator-Prey Dynamics

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Julian Evan Chrisnanto

Salsabila Rahma Alia

Yulison Herry Chrisnanto

415

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16 Sep 2025

Variational Neural Networks for Observable Thermodynamics (V-NOTS)

Variational Neural Networks for Observable Thermodynamics (V-NOTS)

Christopher Eldred

François Gay-Balmaz

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11 Sep 2025

Rollout-LaSDI: Enhancing the long-term accuracy of Latent Space Dynamics

Rollout-LaSDI: Enhancing the long-term accuracy of Latent Space Dynamics

Robert Stephany

154

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09 Sep 2025

BULL-ODE: Bullwhip Learning with Neural ODEs and Universal Differential Equations under Stochastic Demand

BULL-ODE: Bullwhip Learning with Neural ODEs and Universal Differential Equations under Stochastic Demand

Nachiket N. Naik

Prathamesh Dinesh Joshi

Raj Abhijit Dandekar

134

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09 Sep 2025

Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements

Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements

203

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Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification

Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification

Nathan M. Urban

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26 Aug 2025

From Prediction to Simulation: AlphaFold 3 as a Differentiable Framework for Structural Biology

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Fast and Generalizable parameter-embedded Neural Operators for Lithium-Ion Battery Simulation

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The Vanishing Gradient Problem for Stiff Neural Differential Equations

The Vanishing Gradient Problem for Stiff Neural Differential Equations

Linda R. Petzold

235

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Simulation as Supervision: Mechanistic Pretraining for Scientific Discovery

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Reiden Magdaleno

Christopher Harding

Marisa Eisenberg

296

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JAX-MPM: A Learning-Augmented Differentiable Meshfree Framework for GPU-Accelerated Lagrangian Simulation and Geophysical Inverse Modeling

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Universal Differential Equations for Scientific Machine Learning of Node-Wise Battery Dynamics in Smart Grids

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End-to-End Probabilistic Framework for Learning with Hard Constraints

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Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints

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A condensing approach to multiple shooting neural ordinary differential equation

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Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints

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275

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Computational Inertia as a Conserved Quantity in Frictionless and Damped Learning Dynamics

Computational Inertia as a Conserved Quantity in Frictionless and Damped Learning Dynamics

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Automatic and Structure-Aware Sparsification of Hybrid Neural ODEs

Automatic and Structure-Aware Sparsification of Hybrid Neural ODEs

302

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Scientific machine learning in Hydrology: a unified perspective

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136

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A Unified Framework for Simultaneous Parameter and Function Discovery in Differential Equations

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Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification

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J. Blechschmidt

Tom-Christian Riemer

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Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming

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Linus Langenkamp

Philip Hannebohm

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Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning

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679

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Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations

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Anna C. M. Thöni

441

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Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting

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Machine learning identifies nullclines in oscillatory dynamical systems

Machine learning identifies nullclines in oscillatory dynamical systems

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Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout

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Bharat Srikishan

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Impilict Runge-Kutta based sparse identification of governing equations in biologically motivated systems

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Hamidreza Marasi

492

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LeanKAN: A Parameter-Lean Kolmogorov-Arnold Network Layer with Improved Memory Efficiency and Convergence Behavior

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Mechanistic PDE Networks for Discovery of Governing Equations

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Scientific Machine Learning of Flow Resistance Using Universal Shallow Water Equations with Differentiable Programming

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Modelling Chemical Reaction Networks using Neural Ordinary Differential Equations

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Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts

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Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations

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Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks

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