Update about.liquid

Author: anujkarpatne

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           The key motivation behind KGML is to improve the interpretability and generalization power of ML models, especially on out-of-sample distributions and even in the paucity of gold-standard data. 
-          To gain more insight into our research, have a look at this talk given by Anuj Karpatne where he discusses how integrating physics with deep learning can enhance scientific problem-solving, highlighting the limitations of black box methods.
+          To gain more insights into our research, have a look at this recent tutorial given by Anuj Karpatne at the [KGML2024 Workshop](https://sites.google.com/umn.edu/kgml2024/) on the current state and future prospects of research in KGML.
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