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In this [notebook ](https://github.com/DifferentiableUniverseInitiative/flowpm/blob/nbody_ode/notebooks/Simulation-WrongCosmo.ipynb) I try to find the correction terms to compensate for the PM approxi…
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# Title
NODEA - Neural Ordinary Differential Equations Anonymous
# Description
This sessions is supposed to be an introduction to neural ordinary differentiable equations (Neural ODEs). As on…
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Hi, @EmilienDupont , thanks for the code implementation!
I am concerned about the structure implemented in this repo, actually, the architecture in the orginal Neural ODE (chen et al. ) has a featu…
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In the first line of the docs, it says "Physics-Informed Neural Networks for ODE, SDE, RODE, and PDE solving." but I wasn't able to find documentation/examples for SDEs like there are for ODEs and PDE…
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Hello,
I am trying to solve a neural ODE using the `diffrax.ImplicitAdjoint()`, adaptive step sizing and the steady state event as proposed in the documentation. However, I get this error message w…
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This may be of interest.
> Does the use of auto-differentiation yield reasonable updates to deep neural networks that represent neural ODEs? Through mathematical analysis and numerical evidence, we…
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I basically want to implement a non-autonomous neural ode model. The closest one I can find is described in this paper: "Time Dependence in Non-Autonomous Neural ODEs" (https://arxiv.org/pdf/2005.0190…
cyx96 updated
3 years ago
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Adding another feature request since I hear the backend is getting an overhaul :)
It would be great to have support of multiple shooting as it enables parallelization of Neural ODEs + anecdotally i…
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First of all, thank you for this amazing library!
For my own research, I want to test implicit integrators with adjoint sensitivity method to train a neural network. While implicit Euler method pro…
cyx96 updated
2 years ago
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# Description
I would like to create a neural CDE for regression. For that, I have taken the example from [neural CDE for classification](https://docs.kidger.site/diffrax/examples/neural_cde/) and ad…