Update HPO paper and corrected Data Observatory (#1518)

docs/demos/pinn_forward/helmholtz.2d.dirichlet.hpo.rst

@@ -3,7 +3,7 @@ Helmholtz equation over a 2D square domain: Hyper-parameter optimization
 
 Finding proper hyper-parameters for PINNs infrastructures is a common issue for practicioners. To remedy this concern, we apply hyper-parameter optimization (HPO) via Gaussian processes (GP)-based Bayesian optimization.
 
-This example is issued from: *Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems*, [`ArXiv preprint <https://arxiv.org/pdf/2205.06704.pdf>`_].
+This example is issued from: *Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems*, [`Neurocomputing <https://doi.org/10.1016/j.neucom.2023.126826>`_].
 
 Notice that this script can be easilly adapted to other examples (either forward or inverse problems). 
 

docs/user/research.rst

@@ -104,12 +104,12 @@ DeepXDE has been used in
   `Erich Schmid Institute of Materials Science <https://www.oeaw.ac.at/esi/erich-schmid-institute>`_,
   `Athinoula A. Martinos Center for Biomedical Imaging <https://www.martinos.org>`_,
   `Friedrich-Alexander-Universität Erlangen-Nürnberg Research Center for Mathematics of Data <https://mod.fau.eu>`_,
+  `Data Observatory Foundation <https://dataobservatory.net>`_,
   `Fraunhofer Institute for Integrated Systems and Device Technology IISB <https://www.iisb.fraunhofer.de>`_
 - industry, e.g.,
   `Anailytica <https://anailytica.com>`_,
   `Ansys <https://www.ansys.com>`_,
   `BirenTech Research <https://www.birentech.com>`_,
-  `Data Observatory Foundation <https://dataobservatory.net>`_,
   `ExxonMobil <https://corporate.exxonmobil.com>`_,
   `General Motors <https://www.gm.com>`_,
   `RocketML <https://www.rocketml.net>`_,