... |
... |
@@ -14,4 +14,9 @@ |
14 |
14 |
**Level**: beginner(%%) **Type**: interactive tutorial |
15 |
15 |
|
16 |
16 |
This notebook will explain how to optimise a model using the covariance matrix adaptation (CMA) optimisation strategy. BluePyOpt includes two flavors of CMA: a single objective one and a hybrid single/multi objective one. |
|
17 |
+=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] === |
17 |
17 |
|
|
19 |
+**Level**: beginner(%%) **Type**: interactive tutorial |
|
20 |
+ |
|
21 |
+This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt. |
|
22 |
+ |