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"Later on, a lot more could happen in $\\mathcal P$ instead of simply a squaring: we could evaluate finite-difference stencils on the predicted solution, or compute a whole implicit time-integration step of a solver. It's not necessary to make it so simple: the more knowledge and numerical methods we can incorporate, the better we can guide the training process. Not that the square function by PyTorch is already differentiable, and hence represents our \"differentiable solver\" in this example.\n",
"To illustrate this flow process, the next cell shows samples at different times in the flow integration. The initial random distribution slowlyl transforms into the bi-modal one for our parabola targets."
Small typo in:
pbdl-book/intro-teaser.ipynb
Line 298 in 45d2b65
Also here:
pbdl-book/intro-teaser.ipynb
Line 574 in 45d2b65