fixed typo, and script update

diffphys-code-ns.ipynb

@@ -626,7 +626,7 @@
     "This example illustrated how the differentiable physics approach can easily be extended towards significantly more \n",
     "complex PDEs. Above, we've optimized for a mini-batch of 20 steps of a full Navier-Stokes solver.\n",
     "\n",
-    "This is a powerful basis to bring NNs into the picture. As you might have noticed, our degrees of freedom were still a regular grid, and we've jointly solved a single inverse problem. There were three cases to solve as a mini-batch, of course, but nonetheless the setup still represents a direct optimization. Thus, in line with the PINN example of {doc}`physicalloss-code` we've not really dealt with a _machine learning_ task here. However, DP training allows for a range of flexible compinations with NNs that will be the topic of the next chapters.\n"
+    "This is a powerful basis to bring NNs into the picture. As you might have noticed, our degrees of freedom were still a regular grid, and we've jointly solved a single inverse problem. There were three cases to solve as a mini-batch, of course, but nonetheless the setup still represents a direct optimization. Thus, in line with the PINN example of {doc}`physicalloss-code` we've not really dealt with a _machine learning_ task here. However, DP training allows for a range of flexible combinations with NNs that will be the topic of the next chapters.\n"
    ]
   },
   {
@@ -671,4 +671,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
+}

make-pdf.sh

@@ -1,6 +1,7 @@
 # source this file with "." in a shell
 
 # note this script assumes the following paths/versions: python3.7 , /Users/thuerey/Library/Python/3.7/bin/jupyter-book
+# updated for nMBA !
 
 # do clean git checkout for changes from json-cleanup-for-pdf.py via:
 # git checkout diffphys-code-burgers.ipynb diffphys-code-ns.ipynb diffphys-code-sol.ipynb physicalloss-code.ipynb bayesian-code.ipynb supervised-airfoils.ipynb reinflearn-code.ipynb physgrad-code.ipynb physgrad-comparison.ipynb physgrad-hig-code.ipynb
@@ -9,13 +10,17 @@ echo
 echo WARNING - still requires one manual quit of first pdf/latex pass, use shift-x to quit
 echo
 
+PYT=python3.7
+PYT=python3
+
 # warning - modifies notebooks!
-python3.7 json-cleanup-for-pdf.py
+${PYT} json-cleanup-for-pdf.py
 
 # clean / remove _build dir ?
 
 # GEN!
-/Users/thuerey/Library/Python/3.7/bin/jupyter-book build . --builder pdflatex
+#/Users/thuerey/Library/Python/3.7/bin/jupyter-book build . --builder pdflatex
+/Users/thuerey/Library/Python/3.9/bin/jupyter-book build . --builder pdflatex
 
 cd _build/latex
 #mv book.pdf book-xetex.pdf # not necessary, failed anyway
@@ -29,7 +34,7 @@ mv book.aux book-in.aux
 mv book.toc book-in.toc
 #mv sphinxmanual.cls sphinxmanual-in.cls
 
-python3.7 ../../fixup-latex.py
+${PYT} ../../fixup-latex.py
 # reads book-in.tex -> writes book-in2.tex
 
 # remove unicode chars via unix iconv

references.bib

@@ -13,6 +13,15 @@
 @STRING{NeurIPS        = "Advances in Neural Information Processing Systems"}
 
 
+
+@article{prantl2022guaranteed,
+  title={Guaranteed conservation of momentum for learning particle-based fluid dynamics},
+  author={Prantl, Lukas and Ummenhofer, Benjamin and Koltun, Vladlen and Thuerey, Nils},
+  journal={Advances in Neural Information Processing Systems},
+  volume={35},
+  year={2022}
+}
+
 @inproceedings{schnell2022hig,
 	  title={Half-Inverse Gradients for Physical Deep Learning},
 	  author={Schnell, Patrick and Holl, Philipp and Thuerey, Nils},