Added link to ICLR video.
@@ -8,8 +8,9 @@ below](#other-kge-frameworks).
The key goal of LibKGE is to foster *reproducible research* into (as well as
meaningful comparisons between) KGE models and training methods. As we argue in
-our [ICLR 2020 paper](https://github.com/uma-pi1/kge-iclr20), the choice of
-training strategy and hyperparameters are very influential on model performance,
+our [ICLR 2020 paper](https://github.com/uma-pi1/kge-iclr20)
+(see [video](https://iclr.cc/virtual_2020/poster_BkxSmlBFvr.html)), the choice
+of training strategy and hyperparameters are very influential on model performance,
often more so than the model class itself. LibKGE aims to provide *clean
implementations* of training, hyperparameter optimization, and evaluation
strategies that can be used with any model. Every potential knob or heuristic
