Update README.md

Co-authored-by: Thomas Moreau <thomas.moreau.2010@gmail.com>

Author: vloison

README.md

@@ -8,7 +8,7 @@
 This package implements FaDIn and UNHaP. FaDIn and UNHaP are inference methods for parametric Hawkes Processes (HP) with finite-support kernels, with the following features:
 - Computation time is low compared to other methods.
 - Compatible in univariate and multivariate settings.
-- Classical kernels (exponential truncated gaussian, raised cosine) are implemented. The user can add their own kernel for inference. 
+- *Flexible:* Various kernel choices are implemented, with classical ones (exponential, truncated Gaussian, raised cosine) and an API to add custom kernels for inference. 
 - Masking: if only a few Hawkes Parameters need to be inferred, the user can mask the other parameters.
 - Smart initialization of parameters before optimization: the user can choose between `random` (purely random), `moment_matching_max` (moment matching with maximum mode) and `moment_matching_mean` (moment matching with mean mode).