torchdyn 0.1.0 (April 26, 2020)¶
- First commit
torchdyn 0.1.1 (April 30, 2020)¶
- Added new tutorial on integral adjoint training for trajectory tracking
torchdyn 0.2.0 (July 3, 2020)¶
- Introduced new CNF nn.Module for continuous normalizing flows. CNFs disentangle Jacobian trace computation from data-dynamics, allowing for convenient extension to other variants.
- Introduced Stable, HNN, LNN energy models. These wrap the func and handle the additional autograd calls, as well as dimension bookkeeping and concatenation.
- Added several new tutorial notebooks
- New static datasets: gaussians, gaussians_spiral, diffeqml.
- Improved Adjoint to handle both terminal and integral loss functions simultaneously
- Restructured overall API, including NeuralDE
- controlled not a setting anymore: introduction of DataControl module
- order, solver, atol, rtol are now arguments of NeuralDE
- DEFunc is now implicitly called inside the NeuralDE class.
- Slimmed down NeuralDE management of correct ODE solving call.
- New test suite for adjoint, normalizing flows and NeuralDE`.