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Differentiable Programming for Differential Equations: A Review
14 June 2024
Facundo Sapienza
Jordi Bolibar
Frank Schafer
Brian Groenke
Avik Pal
Victor Boussange
Patrick Heimbach
Giles Hooker
Fernando Pérez
Per-Olof Persson
Christopher Rackauckas
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Papers citing
"Differentiable Programming for Differential Equations: A Review"
6 / 6 papers shown
Inferring processes within dynamic forest models using hybrid modeling
Maximilian Pichler
Yannek Käber
238
0
0
02 Aug 2025
JAX-MPM: A Learning-Augmented Differentiable Meshfree Framework for GPU-Accelerated Lagrangian Simulation and Geophysical Inverse Modeling
Honghui Du
QiZhi He
302
2
0
06 Jul 2025
Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints
Avik Pal
Alan Edelman
Christopher Rackauckas
AI4CE
271
6
0
26 May 2025
A Common Interface for Automatic Differentiation
Guillaume Dalle
Adrian Hill
PINN
VLM
314
3
0
08 May 2025
MixFunn: A Neural Network for Differential Equations with Improved Generalization and Interpretability
T. S. Farias
Gubio Gomes de Lima
Jonas Maziero
Celso Jorge Villas-Boas
AI4CE
304
0
0
28 Mar 2025
What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning
Arvind Mohan
Ashesh Chattopadhyay
Jonah Miller
534
4
0
22 Nov 2024
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