torchdyn
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A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
A dynamical system can often be described not by a single tensor but by multiple ones. For example, a system of particles can have node features, edge features, and global...
**Describe the bug** Torchscript is unable to script the `NeuralODE` class due to a function being redefined. This is a problem because there is control flow present in the code...
Clone parts of the `odeint` and ODE solver implementations to get an internal, simplified `sdeint` API. Complete the `EulerMaruyama` placeholder in `solvers.py`.
Standardize the two classes. `NeuralSDE`s should have an option to use our internals or `torchsde` as a backend. Related to [this ](https://github.com/DiffEqML/torchdyn/issues/97) for implementation of our internal solver SDE suite.
I am trying to train a Neural ODE in my local gpu to speed up my training. However, for my surprise it slowed the training rather than speeding it. I...
My code was running fine for older version of torchdyn but I get the above error in the newer version. What has changed in this newer version?
**Additional Description** I have a network I wish to train `f(x, x_dot, theta)` where `x` and `x_dot` are the inputs, `theta` are the network weights. This is a slightly odd...
Add new interpolators and the [Orthogonal Spline Collocation](https://www.sciencedirect.com/science/article/pii/S0377042700005094) under [`torchdyn/numerics/interpolators.py`](https://github.com/DiffEqML/torchdyn/blob/master/torchdyn/numerics/interpolators.py). Would be a fine addition to our collection to add a tutorial as well for the interpolators - in preparation...
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...
Thanks for this amazing package! I was trying to test the memory usage of adjoint, as claimed by authors of the original neural ODE paper, the memory usage of adjoint...