Update docs

Author: lululxvi

README.md

@@ -143,7 +143,7 @@ First off, thanks for taking the time to contribute!
 
 DeepXDE was developed by [Lu Lu](https://lu.seas.upenn.edu) under the supervision of Prof. [George Karniadakis](https://www.brown.edu/research/projects/crunch/george-karniadakis) at [Brown University](https://www.brown.edu) from the summer of 2018 to 2020, supported by [PhILMs](https://www.pnnl.gov/computing/philms). DeepXDE was originally self-hosted in Subversion at Brown University, under the name SciCoNet (Scientific Computing Neural Networks). On Feb 7, 2019, SciCoNet was moved from Subversion to GitHub, renamed to DeepXDE.
 
-DeepXDE is currently maintained by [Lu Lu](https://lu.seas.upenn.edu) at [University of Pennsylvania](https://www.upenn.edu) with major contributions coming from several talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: [Shunyuan Mao](https://github.com/smao-astro), [Zongren Zou](https://github.com/ZongrenZou).
+DeepXDE is currently maintained by [Lu Lu](https://lu.seas.upenn.edu) at [University of Pennsylvania](https://www.upenn.edu) with major contributions coming from several talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: [Zongren Zou](https://github.com/ZongrenZou), [Shunyuan Mao](https://github.com/smao-astro).
 
 ## License
 

docs/user/faq.rst

@@ -3,8 +3,8 @@ FAQ
 
 If you have any questions about DeepXDE, first read the papers/slides and watch the video at the `DeepXDE homepage <https://deepxde.readthedocs.io>`_ and also check the following list of frequently asked DeepXDE questions. To get further help, you can open an issue in the GitHub "Issues" section.
 
-Usage of DeepXDE
-----------------
+General usage
+-------------
 
 - | **Q**: DeepXDE failed to run.
   | **A**: `#2`_, `#3`_, `#5`_
@@ -17,7 +17,7 @@ Usage of DeepXDE
 - | **Q**: How can I use a trained model for new predictions?
   | **A**: `#10`_, `#18`_, `#93`_, `#177`_
 - | **Q**: How can I save a trained model and then load the model later?
-  | **A**: `#54`_, `#57`_, `#58`_, `#63`_, `#103`_, `#206`_, `#254`_
+  | **A**: `#54`_, `#57`_, `#58`_, `#63`_, `#103`_, `#206`_, `#254`_, `#468`_
 - | **Q**: More details about DeepXDE source code, and want to modify DeepXDE.
   | **A**: `#68`_, `#346`_
 
@@ -28,47 +28,55 @@ PINN
   | **A**: `#4`_, `#9`_, `#17`_, `#48`_, `#53`_, `#73`_, `#77`_, `#171`_, `#217`_, `#218`_, `#223`_, `#274`_, `#276`_
 - | **Q**: More details and examples about geometry.
   | **A**: `#32`_, `#38`_, `#161`_, `#264`_, `#278`_, `#332`_
-- | **Q**: How can I implement new ODEs/PDEs, e.g., compute derivatives, complicated PDEs?
-  | **A**: `#12`_, `#13`_, `#21`_, `#22`_, `#74`_, `#78`_, `#79`_, `#124`_, `#172`_, `#185`_, `#193`_, `#194`_, `#246`_, `#302`_, `#377`_, `#421`_, `#451`_, `#465`_
+- | **Q**: How can I implement new ODEs/PDEs, e.g., compute derivatives, complicated PDEs, complicated coefficients?
+  | **A**: `#12`_, `#13`_, `#21`_, `#22`_, `#74`_, `#78`_, `#79`_, `#124`_, `#172`_, `#185`_, `#193`_, `#194`_, `#246`_, `#302`_, `#377`_, `#421`_, `#451`_, `#465`_, `#478`_, `#480`_
 - | **Q**: More details and examples about initial conditions.
-  | **A**: `#19`_, `#75`_, `#104`_, `#134`_, `#398`_
+  | **A**: `#19`_, `#75`_, `#104`_, `#134`_, `#398`_, `#485`_
 - | **Q**: More details and examples about boundary conditions.
-  | **A**: `#6`_, `#10`_, `#15`_, `#16`_, `#22`_, `#26`_, `#33`_, `#38`_, `#40`_, `#44`_, `#49`_, `#115`_, `#140`_, `#156`_, `#352`_, `#365`_, `#457`_
+  | **A**: `#6`_, `#10`_, `#15`_, `#16`_, `#22`_, `#26`_, `#33`_, `#38`_, `#40`_, `#44`_, `#49`_, `#115`_, `#140`_, `#156`_, `#352`_, `#365`_, `#457`_, `#475`_
 - | **Q**: By default, initial/boundary conditions are enforced in DeepXDE as soft constraints. How can I enforce them as hard constraints?
   | **A**: `#36`_, `#90`_, `#92`_, `#252`_
 - | **Q**: How can I use a dataset of the solution?
-  | **A**: `#362`_
+  | **A**: `#362`_, `#487`_
 - | **Q**: I failed to train the network or get the right solution, e.g., large training loss, unbalanced losses.
   | **A**: `#15`_, `#22`_, `#33`_, `#41`_, `#61`_, `#62`_, `#80`_, `#84`_, `#85`_, `#108`_, `#126`_, `#141`_, `#188`_, `#247`_, `#305`_, `#321`_
 - | **Q**: L-BFGS.
   | **A**: `#364`_, `#395`_
 - | **Q**: Implement certain features for the input, such as Fourier features.
-  | **A**: `#277`_
+  | **A**: `#277`_, `#477`_
 - | **Q**: A standard network doesn't work for me, and I want to implement a network with a special structure/property.
-  | **A**: `#355`_, `#363`_
+  | **A**: `#355`_, `#363`_, `#466`_
 - | **Q**: Implement new losses or constraints.
-  | **A**: `#286`_, `#311`_, `#356`_, `#460`_
+  | **A**: `#174`_, `#286`_, `#311`_, `#356`_, `#460`_, `#467`_, `#504`_
 - | **Q**: How can I implement new IDEs?
   | **A**: `#95`_, `#198`_
 - | **Q**: Solve PDEs with complex numbers.
   | **A**: `#284`_
 - | **Q**: Solve inverse problems with unknown parameters/fields in the PDEs or initial/boundary conditions.
   | **A**: `#55`_, `#76`_, `#86`_, `#114`_, `#120`_, `#125`_, `#178`_, `#208`_, `#235`_, `#380`_
 - | **Q**: Solve parametric PDEs.
-  | **A**: `#273`_, `#299`_, `#379`_
+  | **A**: `#273`_, `#299`_, `#379`_, `#482`_
 - | **Q**: How does DeepXDE choose the training points? How can I use some specific training points?
-  | **A**: `#32`_, `#57`_, `#64`_
+  | **A**: `#32`_, `#57`_, `#64`_, `#345`_
 - | **Q**: How can I give different weights to different residual points?
   | **A**: `#45`_
 - | **Q**: Residual-based adaptive refinement (RAR).
   | **A**: `#63`_
 - | **Q**: I want to customize network training/optimization, e.g., mini-batch.
   | **A**: `#166`_, `#307`_, `#320`_, `#331`_
+- | **Q**: I want to get more information about the network, such as the values and gradients of hidden layers.
+  | **A**: `#149`_, `#490`_
 - | **Q**: More details about DeepXDE source code, or I want to modify DeepXDE.
   | **A**: `#35`_, `#39`_, `#66`_, `#69`_, `#91`_, `#99`_, `#131`_, `#163`_, `#175`_, `#202`_, `#357`_
 - | **Q**: Examples collected from users.
   | **A**: `Lotka–Volterra <https://github.com/lululxvi/deepxde/issues/85>`_, `Potential flow around a cylinder <https://github.com/lululxvi/deepxde/issues/49>`_, `Laminar Incompressible flow passing a step <https://github.com/lululxvi/deepxde/issues/80>`_, `Shallow water equations <https://github.com/lululxvi/deepxde/issues/247>`_, `2D time-dependent heat equation <https://github.com/lululxvi/deepxde/issues/61>`_
 
+DeepONet
+--------
+
+- | **Q**:
+  | **A**:
+
 Multi-fidelity NN
 -----------------
 
@@ -152,12 +160,14 @@ Multi-fidelity NN
 .. _#134: https://github.com/lululxvi/deepxde/issues/134
 .. _#140: https://github.com/lululxvi/deepxde/issues/140
 .. _#141: https://github.com/lululxvi/deepxde/issues/141
+.. _#149: https://github.com/lululxvi/deepxde/issues/149
 .. _#156: https://github.com/lululxvi/deepxde/issues/156
 .. _#161: https://github.com/lululxvi/deepxde/issues/161
 .. _#163: https://github.com/lululxvi/deepxde/issues/163
 .. _#166: https://github.com/lululxvi/deepxde/issues/166
 .. _#171: https://github.com/lululxvi/deepxde/issues/171
 .. _#172: https://github.com/lululxvi/deepxde/issues/172
+.. _#174: https://github.com/lululxvi/deepxde/issues/174
 .. _#175: https://github.com/lululxvi/deepxde/issues/175
 .. _#177: https://github.com/lululxvi/deepxde/issues/177
 .. _#178: https://github.com/lululxvi/deepxde/issues/178
@@ -196,6 +206,7 @@ Multi-fidelity NN
 .. _#324: https://github.com/lululxvi/deepxde/issues/324
 .. _#331: https://github.com/lululxvi/deepxde/issues/331
 .. _#332: https://github.com/lululxvi/deepxde/issues/332
+.. _#345: https://github.com/lululxvi/deepxde/issues/345
 .. _#346: https://github.com/lululxvi/deepxde/issues/346
 .. _#352: https://github.com/lululxvi/deepxde/issues/352
 .. _#353: https://github.com/lululxvi/deepxde/issues/353
@@ -218,7 +229,15 @@ Multi-fidelity NN
 .. _#460: https://github.com/lululxvi/deepxde/issues/460
 .. _#464: https://github.com/lululxvi/deepxde/issues/464
 .. _#465: https://github.com/lululxvi/deepxde/issues/465
-
-.. _#149: https://github.com/lululxvi/deepxde/issues/149
-.. _#174: https://github.com/lululxvi/deepxde/issues/174
-.. _#345: https://github.com/lululxvi/deepxde/issues/345
+.. _#466: https://github.com/lululxvi/deepxde/issues/466
+.. _#467: https://github.com/lululxvi/deepxde/issues/467
+.. _#468: https://github.com/lululxvi/deepxde/issues/468
+.. _#475: https://github.com/lululxvi/deepxde/issues/475
+.. _#477: https://github.com/lululxvi/deepxde/issues/477
+.. _#478: https://github.com/lululxvi/deepxde/issues/478
+.. _#480: https://github.com/lululxvi/deepxde/issues/480
+.. _#482: https://github.com/lululxvi/deepxde/issues/482
+.. _#485: https://github.com/lululxvi/deepxde/issues/485
+.. _#487: https://github.com/lululxvi/deepxde/issues/487
+.. _#490: https://github.com/lululxvi/deepxde/issues/490
+.. _#504: https://github.com/lululxvi/deepxde/issues/504

docs/user/team.rst

@@ -3,4 +3,4 @@ The Team
 
 DeepXDE was developed by `Lu Lu <https://lu.seas.upenn.edu>`_ under the supervision of Prof. `George Karniadakis <https://www.brown.edu/research/projects/crunch/george-karniadakis>`_ at `Brown University <https://www.brown.edu>`_ from the summer of 2018 to 2020, supported by `PhILMs <https://www.pnnl.gov/computing/philms>`_. DeepXDE was originally self-hosted in Subversion at Brown University, under the name SciCoNet (Scientific Computing Neural Networks). On Feb 7, 2019, SciCoNet was moved from Subversion to GitHub, renamed to DeepXDE.
 
-DeepXDE is currently maintained by `Lu Lu <https://lu.seas.upenn.edu>`_ at `University of Pennsylvania <https://www.upenn.edu>`_ with major contributions coming from several talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: `Shunyuan Mao <https://github.com/smao-astro>`_, `Zongren Zou <https://github.com/ZongrenZou>`_.
+DeepXDE is currently maintained by `Lu Lu <https://lu.seas.upenn.edu>`_ at `University of Pennsylvania <https://www.upenn.edu>`_ with major contributions coming from several talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: `Zongren Zou <https://github.com/ZongrenZou>`_, `Shunyuan Mao <https://github.com/smao-astro>`_.