From d387e3cc6758e5ad28a814e1a4c127a1b574b06d Mon Sep 17 00:00:00 2001 From: Maziar Raissi Date: Sun, 21 Jan 2018 01:37:07 -0500 Subject: [PATCH] first commit --- docs/_config.yml | 2 +- docs/index.md | 7 +------ 2 files changed, 2 insertions(+), 7 deletions(-) diff --git a/docs/_config.yml b/docs/_config.yml index 3ad7eeaa..bff4ce2c 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -1,3 +1,3 @@ theme: jekyll-theme-cayman title: Physics Informed Neural Networks -description: Deap Learning of Nonlinear Partial Differential Equations +description: Deep Learning of Nonlinear Partial Differential Equations diff --git a/docs/index.md b/docs/index.md index 1c3530d5..55d8a153 100644 --- a/docs/index.md +++ b/docs/index.md @@ -91,12 +91,7 @@ The following figure summarizes our results for the data-driven solution of the ![](http://www.dam.brown.edu/people/mraissi/assets/img/Burgers_CT_inference.png) -
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- Burgers' equation: Top: Predicted solution along with the initial and boundary training data. In addition we are using 10,000 collocation points generated using a Latin Hypercube Sampling strategy. Bottom: Comparison of the predicted and exact solutions corresponding to the three temporal snapshots depicted by the white vertical lines in the top panel. Model training took approximately 60 seconds on a single NVIDIA Titan X GPU card. -
+> Burgers' equation: Top: Predicted solution along with the initial and boundary training data. In addition we are using 10,000 collocation points generated using a Latin Hypercube Sampling strategy. Bottom: Comparison of the predicted and exact solutions corresponding to the three temporal snapshots depicted by the white vertical lines in the top panel. Model training took approximately 60 seconds on a single NVIDIA Titan X GPU card.