update wandb dashboard link on readme

ahenkes1 · Aug 17, 2023 · 7857549 · 7857549
1 parent 37f3854
commit 7857549
Showing 7 changed files with 22 additions and 10 deletions.
diff --git a/examples/adv/README.md b/examples/adv/README.md
@@ -39,7 +39,7 @@ For further details, see the `PeriodEmbs` class.
 
 ### Ablation study
 We conducted an ablation study on **Algorithm 1**, maintaining identical hyperparameters across all tests. The results are displayed in the table below. You can find the specific configuration of the hyperparameters in the `configs` directory. 
-For detailed sweep information, please visit [our Weight & Bias dashboard](https://wandb.ai/jaxpi/adv?workspace=user-sifanw).
+For detailed sweep information, please visit [our Weight & Bias dashboard](https://wandb.ai/jaxpi/adv?workspace=user-).
 
 
 | **Time Period** | **Fourier Feature** | **RWF** | **Grad Norm** | **Causal** | **Rel. $L^2$ Error** | **Runtime (min)** |
@@ -71,7 +71,7 @@ python3 main.py --config/sota.py --mode=eval
 ```
 
 The best relative $L^2$ error is  $6.884\times 10^{-4}$. The figure below shows the exact solution, prediction, and absolute error. 
-The model parameter can be found at [google drive link]. For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](URL2).
+The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/19BEmUYsHWvsj7wgjnpzCxk9NRX70806C?usp=drive_link). For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/adv?workspace=user-).
 
 <figure>
 <img src=figures/adv_pred.png style="width:100%">

diff --git a/examples/allen_cahn/README.md b/examples/allen_cahn/README.md
@@ -15,7 +15,7 @@ $$\begin{aligned}
 
 ### Ablation study
 We conducted an ablation study on **Algorithm 1**, maintaining identical hyperparameters across all tests. The results are displayed in the table below. You can find the specific configuration of the hyperparameters in the `configs` directory. 
-For detailed sweep information, please visit [our Weight & Bias dashboard](https://wandb.ai/jaxpi/allen_cahn?workspace=user-sifanw).
+For detailed sweep information, please visit [our Weight & Bias dashboard](https://wandb.ai/jaxpi/allen_cahn?workspace=user-).
 
 
 | **Ablation Settings** |     |     |     |      **Performance**      |     |
@@ -49,9 +49,9 @@ python3 main.py --config/sota.py --mode=eval
 Our methods have managed to reduce the best relative $L^2$ error to
 $9.55 \times 10^{-5}$. The figure below illustrates the exact solution, our model's prediction, and the absolute error. 
 
-You can access the trained model parameters via [this Google Drive link](URL).
+You can access the trained model parameters via [this Google Drive link](https://drive.google.com/drive/folders/1MJihlw87l9YiVVLA8JBtCubf8PB6hPZY?usp=drive_link).
 
-For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](URL2).
+For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/allen_cahn?workspace=user-).
 
 <figure>
 <img src="figures/ac_pred.png" alt="Allen Cahn equation comparison" style="width:100%">

diff --git a/examples/ks_chaotic/README.md b/examples/ks_chaotic/README.md
@@ -21,7 +21,7 @@ Specifically, we take $\alpha = 100/16, \beta=100/16^2,  \gamma=100/16^4$ and $u
 ## Results
 ### Ablation study
 
-We perform an ablation study on **Algorithm 1**. Table below shows the result of the ablation study. The detail sweep can be found at [weight and bias link](https://wandb.ai/jaxpi/ks?workspace=user-sifanw)
+We perform an ablation study on **Algorithm 1**. Table below shows the result of the ablation study. The detail sweep can be found at [weight and bias link](https://wandb.ai/jaxpi/ks?workspace=user-)
 
 
 | **Modified MLP** | **Fourier Feature** | **RWF** | **Grad Norm** | **Causal** | **Rel. $L^2$ Error** | **Runtime (min)** |
@@ -38,7 +38,7 @@ We perform an ablation study on **Algorithm 1**. Table below shows the result of
 ### State of the art
 
 
-The best relative $L^2$ error is brought down to $1.61 \times 10^{-1}$. The figure below shows the exact solution, prediction, and absolute error. The model parameter can be found at [google drive link]
+The best relative $L^2$ error is brought down to $1.61 \times 10^{-1}$. The figure below shows the exact solution, prediction, and absolute error. The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/1haoDhCUfCq69ptsA2qgiX8yGhwGLbLaT?usp=drive_link)
 
 <figure>
 <img src=figures/ks_chaotic.png style="width:100%">

diff --git a/examples/ldc/README.md b/examples/ldc/README.md
@@ -44,7 +44,8 @@ For the final Re=1000, we perform an ablation study on **Algorithm 1**. Table be
 
 ### State of the art
 
-Taken all together, we present our results for Re=3200.
+Taken all together, we present our results for Re=3200. The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/14bUqullVYHhb68kdwK_lkhzjtvF74nQl?usp=drive_link).
+For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/ldc?workspace=user-).
 
 <figure>
 <img src=figures/ldc_pred.png style="width:100%">

diff --git a/examples/ns_tori/README.md b/examples/ns_tori/README.md
@@ -15,4 +15,9 @@ For this example, we set Re=100 and aim to simulate the system up to T=10.
 
 ## Results
 
+The animation below shows comparison between the exact solution and the prediction.
+The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/1n2k2613BWWLcug3CI4i3ZQnBvgrHS1Ph?usp=drive_link).
+For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/ns_tori?workspace=user-).
+
+
 ![ns_tori](figures/ns_animation.gif)
diff --git a/examples/ns_unsteady_cylinder/README.md b/examples/ns_unsteady_cylinder/README.md
@@ -6,8 +6,12 @@ We follow the problem setup in [here](https://wwwold.mathematik.tu-dortmund.de/~
 
 
 
+
 ## Results
 
+The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/1wy_SJUMPOMFM19P9ChGu_cRlk99VRdZ1?usp=drive_link). For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/ns_unsteady_cylinder?workspace=user-).
+
+
 ![ns_cylinder](figures/ns_cylinder_u.gif)
 
 ![ns_cylinder](figures/ns_cylinder_v.gif)

diff --git a/examples/stokes_cylinder/README.md b/examples/stokes_cylinder/README.md
@@ -38,7 +38,7 @@ where $\mathbf{n}$ denotes the outer normal vector.
 ## Results
 
 ### Ablation study
-We perform an ablation study on **Algorithm 1**. Table below shows the result of the ablation study. The detail training information can be found at [weight and bias link](https://wandb.ai/jaxpi/stokes?workspace=user-sifanw)
+We perform an ablation study on **Algorithm 1**. Table below shows the result of the ablation study. The detail training information can be found at [weight and bias link](https://wandb.ai/jaxpi/stokes?workspace=user-)
 
 
 
@@ -70,7 +70,9 @@ python3 main.py --config/sota.py --mode=eval
 ```
 
 
-The best relative $L^2$ error is brought down to $8.04\times 10^{-5}$. The figure below shows the exact solution, prediction, and absolute error. The model parameter can be found at [google drive link]
+The best relative $L^2$ error is brought down to $8.04\times 10^{-5}$. The figure below shows the exact solution, prediction, and absolute error. 
+The model parameter can be found at [google drive link](https://drive.google.com/drive/folders/11T5ht2LGmIZigIKiLvpyUMbSxlrxb1sF?usp=drive_link).
+For a comprehensive log of the loss and weights, please visit [our Weights & Biases dashboard](https://wandb.ai/jaxpi/stokes?workspace=user-).
 
 <figure>
 <img src=figures/stokes_U.png style="width:100%">