From 0d3848aa59e42b645627168041320a44512f9f28 Mon Sep 17 00:00:00 2001
From: Tizian Wenzel <tizian.wenzel@ians.uni-stuttgart.de>
Date: Fri, 7 Jul 2023 15:19:04 +0200
Subject: [PATCH] Update on README.md
---
README.md | 20 +++++++++++++++++++-
1 file changed, 19 insertions(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 42b4297..2c10b6b 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
Python implementation of the 2L-VKOGA algorithm, which uses a kernel optimization (two layered kernel) before running VKOGA with the modified kernel.
## How to cite:
-If you use this code in your work, please cite the paper
+If you use this code in your work for scalar-valued output data, please cite the paper
> T. Wenzel, F. Marchetti, and E. Perracchione. Data-driven kernel designs for
optimized greedy schemes: A machine learning perspective.
@@ -19,5 +19,23 @@ arXiv preprint arXiv:2301.08047, 2023.
}
```
+If you use this code in your work for vectorial-valued output data, please cite the paper
+
+> T. Wenzel, B. Haasdonk, H. Kleikamp, M. Ohlberger, and F. Schindler. Application
+of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Model-
+ing. arXiv preprint arXiv:2302.14526, 2023. Accepted for LSSC 2023 proceedings.
+
+```bibtex:
+@article{wenzel2023application,
+ title={Application of {D}eep {K}ernel {M}odels for {C}ertified
+and {A}daptive {RB}-{ML}-{ROM} {S}urrogate {M}odeling},
+ author={Wenzel, Tizian and Haasdonk, Bernard and Kleikamp, Hendrik and Ohlberger, Mario and Schindler, Felix},
+ journal={arXiv preprint arXiv:2302.14526},
+ year={2023},
+ note={Accepted for LSSC 2023 proceedings.}
+}
+```
+
+
For further details on the VKOGA algorithm, please refer to [here](https://github.com/GabrieleSantin/VKOGA).
--
GitLab