Update README

ziatdinovmax · Jan 6, 2025 · ffb6a6c · ffb6a6c
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@@ -63,7 +63,12 @@ model.fit(X_measured, y_measured, num_warmup=1000, num_samples=1000)
 
 The obtained posterior means and variances can be used in active learning and Bayesian optimization frameworks. 
 
-An example of applying PBNN to a toy regression problem can be found [here](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/partialBNN_simple_regression.ipynb).
+The following examples demonstrate BNN and PBNN on toy problems:
+
+- Application of Partial and Full BNN to a regression problem: [notebook](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/partialBNN_simple_regression.ipynb)
+- Application of Full BNN to a classification problem: [notebook](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/bnn_simple_classification.ipynb)
+- Application of Partial BNN to a classification problem: [notebook](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/pbnn_simple_classification.ipynb)
+
 
 See also examples of BNN-powered active learning [here](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/bnn_example1d.ipynb) and PBNN-powered active learning [here](https://github.com/ziatdinovmax/NeuroBayes/blob/main/examples/pbnn_example1d.ipynb).