Comments (2)
Is this because of self.integration_time = torch.tensor([0, 1])
, which means only goes to the next "layer" of timestamp 1? So if we define integration_time with [0,1,2], we should add another bunches of parameters like a ResBlock. Not sure.
from torchdiffeq.
Since the dynamics is defined on the hidden state, even a first-order time-invariant ODE can model many types of dynamics, see short discussion in #9. As we use adaptive-step size solvers, integration_time
does not immedately imply the number of discrete steps.
To model time-dependent ODEs, we used multiple approaches to have the output depend on time: see https://github.com/rtqichen/ffjord/blob/master/lib/layers/diffeq_layers/basic.py
from torchdiffeq.
Related Issues (20)
- reuse solver object
- Integrate Forced Andronov-Hopf Bifurcation HOT 3
- Export to ONNX?
- Is func variable in odeint(func, y0, t) the derivative part of the ode?
- Initial Condition changes when calling the odeint_adjoint
- How to use the summary function for model description?
- How to work with control namely PID controller
- Why odeint sometimes provides a wrong solution? HOT 5
- Non uniform time step in example/ode_demo.py
- runtime of ode_demo.py using adjoint vs. not using it HOT 1
- underflow in dt nan HOT 4
- Typo in paper (?) HOT 1
- How to pass extra paramaters of func to odeint? HOT 2
- Bug: Memory Leaky with from torchdiffeq import odeint HOT 1
- Perform one integration step HOT 2
- Scipy LSODA for stiff ODE
- Question about the gradient of `odeint`
- A warning message when there is only 1 evaluation point provided would be helpful
- Enabling Mixed Precision Training for Your Model
- How do I use a solver when input and output shapes don't match?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from torchdiffeq.